🏢 Summary: Full-time Data Analytics Engineer role focused on building and maintaining DBT models in Snowflake, developing Tableau dashboards, and modernizing data infrastructure to support self-serve analytics. The position combines hands-on data modeling, stakeholder ownership, and operational support in a growing US analytics team. Offers competitive salary, stock options, learning budget, comprehensive benefits, and an office-first setup in Boulder. 🗂️ Requirements: Strong experience building or structuring datasets, Solid SQL skills, Hands-on DBT Core experience, Hands-on Snowflake experience, Proven experience building Tableau dashboards, Ability to independently gather requirements and manage stakeholders, High attention to data quality, Experience troubleshooting data pipelines and reporting issues 📃 Skills: SQL, DBT, Snowflake, Tableau, Salesforce, GitHub, Copilot, Cursor, AI, LLMs 🏢 Description: Data Analytics Engineer — Boulder, Colorado Full-time | Boulder, CO | No visa sponsorship available The US Analytics team is building the data foundations that power US operations. We design reliable data models, keep our infrastructure clean, and turn complex datasets into insights the business can act on. You'll join at a point where there's real work to own — from shaping how data is structured to improving the tools and dashboards that teams rely on every day. What you'll do Build, maintain, and document DBT models in a Snowflake environment, keeping data clean, reliable, and well-structured Develop and maintain Tableau dashboards and data sources that stakeholders across the business trust and use independently Rotate through day-to-day data operations support — handling ad hoc requests, troubleshooting reporting issues, and diagnosing pipeline problems Contribute to modernizing our data infrastructure, helping business stakeholders self-serve through AI-assisted tooling Own stakeholder relationships independently — gathering requirements, setting clear expectations, and communicating confidently with technical and non-technical audiences alike You'll be great for this role if… Strong experience building or structuring datasets — not just querying them based on others work Solid SQL, DBT Core skills, hands-on experience with Snowflake Proven ability to build Tableau dashboards that stakeholders genuinely rely on Strong communicator who can own stakeholder conversations, gather requirements, manage expectations, and push back when a request isn't clearly defined High attention to data quality and the confidence to work through problems independently before escalating Familiarity with AI-assisted data tools such as GitHub Copilot or Cursor Familiarity with Salesforce Bonus points for: Advanced DBT experience Experience with self-serve or semantic data layers Contributions to an AI agent knowledge base or prompt engineering work Understanding of the limitations of LLMs when applied to data problems Previous experience in a fast paced, team environment Why you should join Opportunity to work on large-scale fintech products used by millions of businesses worldwide, from the Boulder office in an office-first setup Enrollment onto the Virtual Stock Option program A dedicated annual learning budget of $2,000 for individual development Generous time off: 22 days of paid vacation, plus an extra day each year up to 28 days, public holidays, and special leaves Health and life coverage: group medical coverage, plus life insurance 401(k) retirement scheme with matching funds 1-month sabbatical after 3 years of service Commitment to Diversity and Inclusion Compensation: $100,000–$120,000 base salary Final compensation will be based on the candidate's experience and location

🏢 Summary: Analytics Engineer role focused on building scalable healthcare data products and analytics-ready models for PBM and care navigation operations using dbt, SQL, and cloud data platforms. The position involves developing reliable data pipelines, implementing data quality frameworks, and enabling self-service and AI-assisted analytics capabilities. Candidates will collaborate across technical and business teams to create maintainable, auditable, and high-performance data solutions. 🗂️ Requirements: 3+ years experience in analytics engineering, data modeling, data warehousing or related field, Strong experience with dbt, Advanced SQL proficiency, Experience developing data transformations and workflows using Python, Understanding of dimensional modeling and scalable data architecture, Experience building production-grade data models and data quality tests, Experience with cloud data warehouses, Experience orchestrating and monitoring data pipelines, Experience working in cloud environments, Familiarity with Git and CI/CD workflows, Knowledge of testing and deployment workflows, Strong problem-solving and analytical skills, Effective communication and collaboration skills 📃 Skills: dbt, SQL, Python, Redshift, Snowflake, BigQuery, Airflow, Dagster, AWS, Git, CI/CD, MCP, Claude 🏢 Description: ABOUT THE ROLE: We are seeking an Analytics Engineer to join our Analytics Platform team to design, build and maintain scalable data products that power our Pharmacy Benefit Management (PBM) and Care Navigation organizations. In this role, you will be responsible for transforming complex healthcare data into trusted, analytics ready datasets that support operational reporting, client insights, financial analysis and strategic decision-making. You will partner closely with Analytics, Data Engineering, Clinical, Client Success, Product and Operations teams to build reliable and scalable data models within our data foundry. This role is ideal for someone who is passionate about analytics engineering, has strong dbt expertise, enjoys solving complex healthcare data challenges and thinks beyond individual requests to build reusable and maintainable systems. You will play a key role in shaping the future of our data platform by developing high-quality data products, establishing engineering best practices, and helping the organization evolve toward AI-enabled and self-service analytics capabilities. WHAT YOU'LL DO: • Apply hands on analytics and data expertise to solve complex, fast moving financial and operational problems in the health tech space • Design, develop and maintain scalable, analytics ready data models (primarily in dbt) that power a PBM and care navigation data ecosystem that support client reporting, performance analytics, operational analysis and self-service business intelligence • Translate complex pharmacy benefits and healthcare navigation workflows, business rules and operational processes into transparent, maintainable, and auditable data models • Partner closely with data and analytics engineers, data analysts and business stakeholders to deliver reliable data products that can be leveraged across multiple use cases and continuously optimize data models and warehouse performance to support large-scale PBM/care navigation datasets and growing business needs • Implement automated data quality checks, testing frameworks and reconciliation processes to ensure data reliability • Establish documentation standards, lineage and analytics engineering guardrails that promote transparency and auditability • Contribute to engineering best practices including version control, CI/CD, incremental models, code reviews, and observability • Contribute to data governance by establishing modeling standards, documentation and guardrails that support auditability, explainability and long term maintainability • Build data foundations that enable future agentic analytics engineering use cases, including self-service analytics and AI-assisted insight generation • Stay informed on emerging technologies and identify opportunities to incorporate AI into analytics engineering workflows WHO YOU ARE: • 3+ years of experience in analytics engineering, data modeling, data warehousing or a related field • Strong experience with dbt and modern analytics engineering best practices (required) • Advanced SQL proficiency and experience developing data transformations and workflows using Python • Strong understanding of dimensional modeling, medallion architecture, semantic modeling and scalable data architecture principles • Experience building and maintaining production-grade data models, data quality tests, and documentation • Experience working with cloud data warehouses such as Amazon Redshift, Snowflake, or BigQuery • Experience orchestrating and monitoring data pipelines using tools such as Apache Airflow, Dagster etc. • Experience working within cloud environments, preferably AWS • Familiarity with software engineering practices including Git, CI/CD, pull request reviews, testing, and deployment workflows • Interest or experience in leveraging AI-enabled development workflows and analytics tooling, including experience with or willingness to learn technologies such as Claude, Claude Skills, Model Context Protocol (MCP) and AI assisted engineering practices • Strong problem-solving and analytical skills with a focus on building scalable, maintainable data solutions • Effective communication skills and the ability to collaborate with both technical and non-technical stakeholders COMPENSATION: $100,000 - $140,000 annually, in addition to bonus and equity. Compensation offered will be determined by geographic location, experience, and qualifications.

🏢 Summary: Senior BI and Analytics Engineer responsible for building and optimizing scalable data tools and pipelines within a modern data stack to deliver trusted, high-quality insights across the organization. The role focuses on SQL-driven analytics, data modeling, DataOps practices, and cross-functional collaboration to enable data-driven decision-making. You will develop robust data transformations, maintain data quality, and create impactful dashboards and reverse ETL workflows. 🗂️ Requirements: BSc/MA in Computer Science, Statistics, Math, Engineering or related quantitative field, Minimum 4 years experience in analytics engineering, data engineering, data analytics or related field, Advanced SQL expertise, Experience with in-warehouse transformation tools (dbt preferred), Experience designing and querying OLAP data warehouses (Snowflake or BigQuery), Minimum 1 year experience with BI tools (Looker preferred), Experience with dimensional data modeling (Kimball or Data Vault), Experience building and maintaining data pipelines, Command line proficiency, Git version control experience 📃 Skills: SQL, dbt, Snowflake, BigQuery, Looker, Airflow, FiveTran, OLAP, Kimball, DataVault, Git, Bash, Python, Docker, Kubernetes, ECS, Snowplow 🏢 Description: Who are we and why should you join us? BetterHelp is on a mission to remove the traditional barriers to therapy and make mental health care more accessible to everyone. Founded in 2013, we are now the world's largest online therapy service, providing affordable and convenient therapy in across the globe. Our network of over 30,000 licensed therapists has helped millions of people take ownership of their mental health and change their lives forever. And we're not stopping there – as the unmet need for mental health services continues to grow, BetterHelp is committed to being part of the solution. As a Senior BI and Analytics Engineer at BetterHelp, you'll join a diverse team of licensed clinicians, engineers, product pros, creatives, marketers, and business leaders who share a passion for expanding access to therapy. And as a mental health company, we take employee mental health just as seriously as we do our mission. We deeply invest in our team's well-being and professional development, because we know that business and individual growth go hand-in-hand. At BetterHelp, you'll carve your own path, make an immediate impact, and be challenged every day – with a supportive community behind you the whole way. What are we looking for? We are looking for a Senior Business Intelligence and Analytics Engineer to help us in developing best in class data tools to deliver high quality tools and services and maintain our accelerated growth. These tools must be developed and maintained using best practices to ensure scalability and stakeholder trust as we grow in both size and scope. You will work cross functionally closely with both technical and business stakeholders across the company, as well as optimize our data stack for delivering trustworthy, discoverable, impactful data to fit their needs. What will you do? Act as a subject matter expert (SME) and deliver training to the cross functional teams to enable business users to make data-driven decisions. Deliver direct analytical insights like dashboards and ad-hoc analyses to business stakeholders Collaborate with the teams across the company to understand their use cases and deliver high value data tools Live and breathe SQL Ensure data quality and freshness at every step of the pipeline for data trust and consistency Create reverse ETL flows to make modeled data directly to stakeholders in the tools they use to foster fast and informed decision making Define and build robust DataOps pipelines and data expectations to ensure the effective delivery of data to all internal data services Explore, propose, and integrate new data sources and software solutions into the reporting environment Contribute to data-driven culture at BetterHelp by directly training stakeholders as well as creating resources such as documentation for empowering others to perform their own analyses Enjoy great teamwork, have lots of fun, and take pride in building a world-class product that makes a difference in people's lives. Partner with data and machine learning engineers and work with a modern data stack: Airflow, FiveTran, Snowflake, dbt, and Looker What will you NOT do? You will NOT worry about "runway", "cash left", or "how much time we have until the next round". We have the startup DNA but we're fully backed and funded, all the way to success. You will NOT be confined to your "job". You will get involved in product, marketing, business strategy, and almost everything we do. You will NOT be bogged down by office politics, ego, or bad attitude. Only positive, pleasure-to-work-with people are allowed here! You will NOT get yourself burned out. We work hard but we believe in maintaining a sustainable work/life balance. Really. Can I work remotely? Yes. We operate on PST and candidates in any time zone are welcome to apply. We ask employees to travel to our San Jose, CA office up to three times per year plus one company-wide offsite to collaborate in person and strengthen working relationships. Travel expenses are covered and reasonable accommodations are made for those under unique circumstances who cannot travel. Requirements BSc/MA in a quantitative discipline such as Computer Science, Statistics, Math, or Engineering At least 4 years of experience in an analytics engineering, data engineering, data analytics, or a related field Advanced experience working with data pipeline tools, particularly in-warehouse transformation tools (preferably dbt) Advanced experience with SQL Experience querying and designing performant tables within OLAP data warehouses (e.g. Snowflake, BigQuery) At least 1 year experience working & developing with BI Tools (preferably Looker) Familiarity with frameworks and tradeoffs in building complex data models, preferably working work dimensional modeling frameworks (e.g. Kimball, Data Vault) Excellent communication (oral and written), attention to detail, time management and organizational skills Experience and comfort using the command line Experience using git for version control Bonus (Great to have, but not required) Familiarity with patterns for handling large-scale data transformations (e.g. dbt incremental models, horizontal/vertical scaling big data patterns) Experience working with Python-based workflow orchestration tools (e.g. Airflow) Experience working with Docker and container orchestration (e.g. Kubernetes, ECS) Experience with web-based B2C, marketplace products Familiarity with web event tracking tools like Snowplow Experience defining and building DataOps practices and deployment strategies Experience defining data governance procedures & working with data catalogs Benefits Remote work with regular in-person bonding experiences sponsored by the company Competitive compensation Holistic perks program (including free therapy, employee wellness, and more) Excellent health, dental, and vision coverage 401k benefits with employer matching contribution The chance to build something that changes lives – and that people love Any piece of hardware or software that will make you happy and productive An awesome community of co-workers The base salary range for this position is $100,000 - $155,000 In addition to the base salary, this position is eligible for a performance bonus and the extensive benefits listed here (subject to eligibility requirements): Teladoc Health Benefits 2025. Total compensation is based on several factors – including, but not limited to, type of position, location, education level, work experience, and certifications. This information is applicable to all full-time positions. At BetterHelp we thrive on difference and individuality, and as part of the Teladoc Health family, we are proud to be an Equal Opportunity Employer. We never have and never will discriminate against any job candidate or employee due to age, race, ethnicity, religion, sex, color, national origin, gender, gender identity, sexual orientation, medical condition, marital status, parental status, disability, or Veteran status.

🏢 Summary: Remote Data Engineer role focused on building and evolving an internal data platform that enables secure, governed, and scalable access to data for software development and analytics teams. The position involves designing, implementing, and maintaining AWS-based data infrastructure, data pipelines, and platform services while ensuring compliance, resiliency, and automation. The role also includes architectural improvements, mentorship, and driving best practices in modern data architectures. 🗂️ Requirements: B.S. in Computer Science or equivalent experience, 4+ years of SQL experience, 4+ years of relational database design and programming (PostgreSQL, MySQL), Experience managing AWS data infrastructure (S3, RDS, Kafka, Glue, Athena, etc.), Experience in software development or systems engineering (Java, JavaScript, Python, PHP), Experience with modern API platform design and security practices, Knowledge of event-driven architecture and change data capture, Legal authorization to work in the United States without visa sponsorship 📃 Skills: SQL, PostgreSQL, MySQL, PL/pgSQL, AWS, S3, RDS, Kafka, Glue, Athena, Quicksight, DataZone, Java, JavaScript, Python, PHP, API, CI/CD, Docker, Kubernetes, Terraform, NetSuite, Salesforce, Workday, Pendo, Grafana, Kibana, Elasticsearch, OpenTelemetry, ETL, Boomi, HIPAA, PCI, SEC, FINRA, Agile, Kanban 🏢 Description: About SRS Acquiom SRS Acquiom delivers the smartest way to run a deal™ through a platform and services designed to help deal parties manage complex M&A and loan agency transactions more efficiently. Based in Denver, Colorado, with offices across the United States and in London and Amsterdam, SRS Acquiom supports transactions across North America and Europe. Our M&A services include professional shareholder representation, paying and escrow agent services, and online document solicitation and reporting. For loan and credit transactions, we provide independent Administrative Agent, Collateral Agent, Sub-Agent, and Successor Agent services. Since 2007, SRS Acquiom has supported more than 11,500 transactions globally. By bringing efficiency, expertise, and purpose-built technology to complex financial transactions, we help sophisticated deal parties focus on building great businesses and maximizing value. We're equally committed to building careers as we are to building solutions. If you're looking for a company with entrepreneurial energy, a proven record of growth and innovation, and a culture that supports your next career move, we'd love to talk. A few benefits our employees enjoy Day‑one coverage: medical, dental, and vision plans so you're protected from the start A 401(k) with a 4% company match to keep your future on track Discretionary time off - take the time you need, when you need it Employer‑paid life insurance, with the option to add extra coverage for peace of mind Employee Assistance Programs for confidential support when life gets complicated Discounted pet insurance (because furry family members count, too) A fitness credit to back your health and wellness goals Pre‑tax plans for dependent care, transportation, and flexible spending Position Summary We are growing our Platform Engineering team and are looking to add a Data Engineer who will be able to help build our internal data platform. This data platform is central to ensuring that our software development and data analytics teams have governed access to the data they need. As a Data Engineer on the Platform Team, you will be a part of driving the design, development, and implementation of our data platforms. Your responsibilities include partnering with the architect and engineering teams in developing our platform, as well as providing best practices and approaches to ensure security, resiliency, and availability of solutions. You will be challenged to create strategies that ensure the secure consumption of the platform through continuous innovation, simplification, and self-service automation. Location: This position is fully remote within the Continental United States. In-person visits to the Denver headquarters are required, on average three times per year. Compensation: The salary range for this position is between $125k and $140k, depending on experience level. Primary Responsibilities Participate in all initiatives keeping all compliance, security and regulatory needs satisfied Be a thought leader by staying abreast of current and emerging technologies and industry trends. Work with your peers to design and build data platform capabilities and incorporate the necessary automations and tool configurations that ensure agile delivery and secure consumption Design and implement processes and tools that enable product engineering and BI/Analytics teams to consume an extensible and scalable data platform, which enforces all needed governance and consistent operational models Be a trusted advisor for initiatives by providing objective, practical, and relevant ideas, insights, and advice while also building organizational partnerships and networks to ensure comprehensive capabilities are developed with input from appropriate business and Engineering resources Directly support the use and delivery of data platform services in the organization Ensure that all data platform solutions follow established security and compliance controls Maintain existing and future software services code and configuration Make recommendations for improvements to existing architecture Help implement new technologies for future deployment Provide technical guidance, knowledge transfers, and mentorship to clients on their data platform adoption Help implement and improve the development of data pipelines Other duties as assigned Required Qualifications & Skills B.S. in Computer Science or equivalent experience 4+ years of experience with and strong working knowledge of SQL required, and understanding of data models 4+ years of experience with or strong knowledge of Postgresql, MySQL, or other relational database design and programming: stored procedures, functions, PL/pgSQL Experience with or working knowledge of managing AWS Data Infrastructure: S3, RDS, Managed Streaming Kafka, Lake Formation, Glue, Glue Data Catalog, Athena, Quicksight, DataZone Experience with systems engineering and/or software development: Java, Javascript, Python, PHP Experience with modern API platform design, security practices, and data architectures: event-driven architecture, change data capture, pub/sub Preferred Qualifications & Skills Experience with cloud solution design patterns: CI/CD, Docker, Kubernetes, containers, microservices, distributed caching Experience with Terraform scripting Experience with data integrations from third-party platforms: NetSuite, Salesforce, Workday, Pendo Experience with reporting and analytic tools: Grafana, Kibana, Elasticsearch, Open Telemetry Experience with ETL processes, projects, and tooling: Boomi Understanding of systems hardening and secure systems configuration Experience with regulatory compliance standards: HIPAA, PCI, SEC, FINRA Excellent written and verbal communication skills, with the ability to present complex technical information in a clear and concise manner to a variety of audiences Understanding of Agile/Kanban methodologies Desired Characteristics Self-motivated Intellectually curious Collaborative Amiable Operates with the highest integrity and attention to detail Passionate about efficient, scalable business processes Ability to prioritize and multitask across many projects Physical Requirements/Special Demands Must be available to work standard business hours and occasional nights/weekends. Travel is required up to three times per year ** We are unable to sponsor or take over sponsorship of employment visas. Candidates must be legally authorized to work in the United States without the need for current or future visa sponsorship to move forward in the hiring process. ** Fraud & spam screening. We use tools in our applicant tracking system to help detect potentially fraudulent or spam applications. These tools analyze limited technical and contact information (such as IP address, device/browser signals, and email/phone characteristics) to flag patterns that may indicate automated, inauthentic, or suspicious activity. Flags are used to prioritize human review and do not, by themselves, determine hiring outcomes. Learn more in our Privacy Policy. This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee. Duties, responsibilities, and activities may change, or new ones may be assigned at any time with or without advanced notice. With respect to its programs, services, activities, and employment practices, SRS Acquiom Inc. assesses qualified individuals without regard to their race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), age, national origin, disability, veteran status, genetic information, or other protected status. Requests for reasonable accommodation or the provision of auxiliary aids should be directed to Human Resources.

🏢 Summary: Analytics Engineer role focused on building scalable healthcare data products and analytics-ready datasets for PBM and care navigation systems. The position involves developing dbt-based data models, optimizing cloud data warehouses, implementing data quality frameworks, and enabling AI-assisted analytics capabilities. Candidates will collaborate across analytics, engineering, product, and operations teams to support reporting, operational analysis, and self-service business intelligence. 🗂️ Requirements: 3+ years experience in analytics engineering, data modeling, or data warehousing, Strong dbt expertise, Advanced SQL proficiency, Experience with Python data transformations and workflows, Knowledge of dimensional modeling and scalable data architecture, Experience with production-grade data models and data quality testing, Experience with cloud data warehouses, Experience orchestrating data pipelines, Experience working in AWS environments, Familiarity with Git and CI/CD workflows, Knowledge of testing and deployment workflows, Strong analytical and problem-solving skills, Ability to collaborate with technical and non-technical stakeholders 📃 Skills: dbt, SQL, Python, Redshift, Snowflake, BigQuery, Airflow, Dagster, AWS, Git, CI/CD, MCP, Claude 🏢 Description: ABOUT THE ROLE: We are seeking an Analytics Engineer to join our Analytics Platform team to design, build and maintain scalable data products that power our Pharmacy Benefit Management (PBM) and Care Navigation organizations. In this role, you will be responsible for transforming complex healthcare data into trusted, analytics ready datasets that support operational reporting, client insights, financial analysis and strategic decision-making. You will partner closely with Analytics, Data Engineering, Clinical, Client Success, Product and Operations teams to build reliable and scalable data models within our data foundry. This role is ideal for someone who is passionate about analytics engineering, has strong dbt expertise, enjoys solving complex healthcare data challenges and thinks beyond individual requests to build reusable and maintainable systems. You will play a key role in shaping the future of our data platform by developing high-quality data products, establishing engineering best practices, and helping the organization evolve toward AI-enabled and self-service analytics capabilities. WHAT YOU'LL DO: Apply hands on analytics and data expertise to solve complex, fast moving financial and operational problems in the health tech space Design, develop and maintain scalable, analytics ready data models (primarily in dbt) that power a PBM and care navigation data ecosystem that support client reporting, performance analytics, operational analysis and self-service business intelligence. Translate complex pharmacy benefits and healthcare navigation workflows, business rules and operational processes into transparent, maintainable, and auditable data models. Partner closely with data and analytics engineers, data analysts and business stakeholders to deliver reliable data products that can be leveraged across multiple use cases and continuously optimize data models and warehouse performance to support large-scale PBM/care navigation datasets and growing business needs. Implement automated data quality checks, testing frameworks and reconciliation processes to ensure data reliability. Establish documentation standards, lineage and analytics engineering guardrails that promote transparency and auditability. Contribute to engineering best practices including version control, CI/CD, incremental models, code reviews, and observability. Contribute to data governance by establishing modeling standards, documentation and guardrails that support auditability, explainability and long term maintainability. Build data foundations that enable future agentic analytics engineering use cases, including self-service analytics and AI-assisted insight generation. Stay informed on emerging technologies and identify opportunities to incorporate AI into analytics engineering workflows. WHO YOU ARE: 3+ years of experience in analytics engineering, data modeling, data warehousing or a related field. Strong experience with dbt and modern analytics engineering best practices (required). Advanced SQL proficiency and experience developing data transformations and workflows using python. Strong understanding of dimensional modeling, medallion architecture, semantic modeling and scalable data architecture principles. Experience building and maintaining production-grade data models, data quality tests, and documentation. Experience working with cloud data warehouses such as Amazon Redshift, Snowflake, or BigQuery. Experience orchestrating and monitoring data pipelines using tools such as Apache Airflow., Dagster etc. Experience working within cloud environments, preferably AWS. Familiarity with software engineering practices including Git, CI/CD, pull request reviews, testing, and deployment workflows. Interest or experience in leveraging AI-enabled development workflows and analytics tooling, including experience with or willingness to learn technologies such as claude, claude skills, Model Context Protocol (MCP) and AI assisted engineering practices. Strong problem-solving and analytical skills with a focus on building scalable, maintainable data solutions. Effective communication skills and the ability to collaborate with both technical and non-technical stakeholders. COMPENSATION: $100,000 - $140,000 annually, in addition to bonus and equity Compensation offered will be determined by geographic location, experience, and qualifications.CYBERSECURITY AWARENESS NOTICE In response to ongoing and industry-wide fraudulent recruitment activities (i.e., job scams), Rightway wants to inform potential candidates that we will only contact them from the @rightwayhealthcare.com email domain. We will never ask for bank details or deposits of any kind as a condition of employment. ABOUT RIGHTWAY: Rightway is on a mission to harmonize healthcare for everyone, everywhere. Our products guide patients to the best care and medications by inserting clinicians and pharmacists into a patient's care journey through a modern, mobile app. Rightway is a front door to healthcare, giving patients the tools they need along with on-demand access to Rightway health guides, human experts that answer their questions and manage the frustrating parts of healthcare for them. Since its founding in 2017, Rightway has raised over $200mm from investors including Khosla Ventures, Thrive Capital, and Tiger Global. We're headquartered in New York City, with satellite offices in Denver and Dallas. Our clients rely on us to transform the healthcare experience, improve outcomes for their teams, and decrease their healthcare costs. HOW WE LIVE OUR VALUES TO OUR TEAMMATES: We're seeking those with passion for healthcare and relentless devotion to our goal. We need team members that embody our core values: 1) We are human, firstOur humanity binds us together. We bring the same empathetic approach to every individual we engage with, whether it be our members, our clients, or each other. We are all worthy of respect and understanding and we engage in our interactions with care and intention. We honor our stories. We listen to—and hear—each other, we celebrate our differences and similarities, we are present for each other, and we strive for mutual understanding. 2) We redefine what is possibleWe always look beyond the obstacles in front of us to imagine new solutions. We approach our work with inspiration from other industries, other leaders, and other challenges. We use ingenuity and resourcefulness when faced with tough problems. 3) We debate then commitWe believe that a spirit of open discourse is part of a healthy culture. We understand and appreciate different perspectives and we challenge our assumptions. When working toward a decision or a new solution, we actively listen to one another, approach it with a "yes, and" mentality, and assume positive intent. Once a decision is made, we align and champion it as one team. 4) We cultivate gritChanging healthcare doesn't happen overnight. We reflect and learn from challenges and approach the future with a determination to strive for better. In the face of daunting situations, we value persistence. We embrace failure as a stepping stone to future success. On this journey, we seek to act with guts, resilience, initiative, and tenacity. 5) We seek to delightHealthcare is complicated and personal. We work tirelessly to meet the goals of our clients while also delivering the best experience to our members. We recognize that no matter the role or team, we each play a crucial part in our members' care and take that responsibility seriously. When faced with an obstacle, we are kind, respectful, and solution-oriented in our approach. We hold ourselves accountable to our clients and our members' success. Rightway is proud to be an Equal Opportunity Employer that believes in the strength of diverse thought, beliefs, backgrounds, and education. We foster an inclusive culture where differences are celebrated to drive the best business decisions possible. We do not discriminate on any basis protected by applicable law. All employment decisions are based on merit, qualifications, need, and performance.

🏢 Summary: Analytics Engineer role focused on building scalable healthcare data products and analytics-ready datasets for PBM and care navigation operations. The position emphasizes dbt-based data modeling, cloud data warehousing, automated data quality processes, and collaboration across analytics, engineering, and business teams. The role also supports AI-enabled analytics capabilities and self-service data platforms. 🗂️ Requirements: 3+ years experience in analytics engineering, data modeling, data warehousing or related field, Strong experience with dbt, Advanced SQL proficiency, Experience developing data transformations and workflows with Python, Understanding of dimensional modeling and scalable data architecture, Experience building production-grade data models and data quality tests, Experience with cloud data warehouses, Experience orchestrating and monitoring data pipelines, Experience working in cloud environments, Familiarity with Git and CI/CD workflows, Experience with testing and deployment workflows, Strong problem-solving and analytical skills, Ability to collaborate with technical and non-technical stakeholders 📃 Skills: dbt, SQL, Python, Redshift, Snowflake, BigQuery, Airflow, Dagster, AWS, Git, CI/CD, MCP, Claude 🏢 Description: ABOUT THE ROLE: We are seeking an Analytics Engineer to join our Analytics Platform team to design, build and maintain scalable data products that power our Pharmacy Benefit Management (PBM) and Care Navigation organizations. In this role, you will be responsible for transforming complex healthcare data into trusted, analytics ready datasets that support operational reporting, client insights, financial analysis and strategic decision-making. You will partner closely with Analytics, Data Engineering, Clinical, Client Success, Product and Operations teams to build reliable and scalable data models within our data foundry. This role is ideal for someone who is passionate about analytics engineering, has strong dbt expertise, enjoys solving complex healthcare data challenges and thinks beyond individual requests to build reusable and maintainable systems. You will play a key role in shaping the future of our data platform by developing high-quality data products, establishing engineering best practices, and helping the organization evolve toward AI-enabled and self-service analytics capabilities. WHAT YOU'LL DO: Apply hands on analytics and data expertise to solve complex, fast moving financial and operational problems in the health tech space Design, develop and maintain scalable, analytics ready data models (primarily in dbt) that power a PBM and care navigation data ecosystem that support client reporting, performance analytics, operational analysis and self-service business intelligence. Translate complex pharmacy benefits and healthcare navigation workflows, business rules and operational processes into transparent, maintainable, and auditable data models. Partner closely with data and analytics engineers, data analysts and business stakeholders to deliver reliable data products that can be leveraged across multiple use cases and continuously optimize data models and warehouse performance to support large-scale PBM/care navigation datasets and growing business needs. Implement automated data quality checks, testing frameworks and reconciliation processes to ensure data reliability. Establish documentation standards, lineage and analytics engineering guardrails that promote transparency and auditability. Contribute to engineering best practices including version control, CI/CD, incremental models, code reviews, and observability. Contribute to data governance by establishing modeling standards, documentation and guardrails that support auditability, explainability and long term maintainability. Build data foundations that enable future agentic analytics engineering use cases, including self-service analytics and AI-assisted insight generation. Stay informed on emerging technologies and identify opportunities to incorporate AI into analytics engineering workflows. WHO YOU ARE: 3+ years of experience in analytics engineering, data modeling, data warehousing or a related field. Strong experience with dbt and modern analytics engineering best practices (required). Advanced SQL proficiency and experience developing data transformations and workflows using python. Strong understanding of dimensional modeling, medallion architecture, semantic modeling and scalable data architecture principles. Experience building and maintaining production-grade data models, data quality tests, and documentation. Experience working with cloud data warehouses such as Amazon Redshift, Snowflake, or BigQuery. Experience orchestrating and monitoring data pipelines using tools such as Apache Airflow., Dagster etc. Experience working within cloud environments, preferably AWS. Familiarity with software engineering practices including Git, CI/CD, pull request reviews, testing, and deployment workflows. Interest or experience in leveraging AI-enabled development workflows and analytics tooling, including experience with or willingness to learn technologies such as claude, claude skills, Model Context Protocol (MCP) and AI assisted engineering practices. Strong problem-solving and analytical skills with a focus on building scalable, maintainable data solutions. Effective communication skills and the ability to collaborate with both technical and non-technical stakeholders. COMPENSATION: $100,000 - $140,000 annually, in addition to bonus and equity Compensation offered will be determined by geographic location, experience, and qualifications.CYBERSECURITY AWARENESS NOTICE In response to ongoing and industry-wide fraudulent recruitment activities (i.e., job scams), Rightway wants to inform potential candidates that we will only contact them from the @rightwayhealthcare.com email domain. We will never ask for bank details or deposits of any kind as a condition of employment. ABOUT RIGHTWAY: Rightway is on a mission to harmonize healthcare for everyone, everywhere. Our products guide patients to the best care and medications by inserting clinicians and pharmacists into a patient's care journey through a modern, mobile app. Rightway is a front door to healthcare, giving patients the tools they need along with on-demand access to Rightway health guides, human experts that answer their questions and manage the frustrating parts of healthcare for them. Since its founding in 2017, Rightway has raised over $200mm from investors including Khosla Ventures, Thrive Capital, and Tiger Global. We're headquartered in New York City, with satellite offices in Denver and Dallas. Our clients rely on us to transform the healthcare experience, improve outcomes for their teams, and decrease their healthcare costs. HOW WE LIVE OUR VALUES TO OUR TEAMMATES: We're seeking those with passion for healthcare and relentless devotion to our goal. We need team members that embody our core values: 1) We are human, firstOur humanity binds us together. We bring the same empathetic approach to every individual we engage with, whether it be our members, our clients, or each other. We are all worthy of respect and understanding and we engage in our interactions with care and intention. We honor our stories. We listen to—and hear—each other, we celebrate our differences and similarities, we are present for each other, and we strive for mutual understanding. 2) We redefine what is possibleWe always look beyond the obstacles in front of us to imagine new solutions. We approach our work with inspiration from other industries, other leaders, and other challenges. We use ingenuity and resourcefulness when faced with tough problems. 3) We debate then commitWe believe that a spirit of open discourse is part of a healthy culture. We understand and appreciate different perspectives and we challenge our assumptions. When working toward a decision or a new solution, we actively listen to one another, approach it with a "yes, and" mentality, and assume positive intent. Once a decision is made, we align and champion it as one team. 4) We cultivate gritChanging healthcare doesn't happen overnight. We reflect and learn from challenges and approach the future with a determination to strive for better. In the face of daunting situations, we value persistence. We embrace failure as a stepping stone to future success. On this journey, we seek to act with guts, resilience, initiative, and tenacity. 5) We seek to delightHealthcare is complicated and personal. We work tirelessly to meet the goals of our clients while also delivering the best experience to our members. We recognize that no matter the role or team, we each play a crucial part in our members' care and take that responsibility seriously. When faced with an obstacle, we are kind, respectful, and solution-oriented in our approach. We hold ourselves accountable to our clients and our members' success. Rightway is proud to be an Equal Opportunity Employer that believes in the strength of diverse thought, beliefs, backgrounds, and education. We foster an inclusive culture where differences are celebrated to drive the best business decisions possible. We do not discriminate on any basis protected by applicable law. All employment decisions are based on merit, qualifications, need, and performance.

🏢 Summary: Analytics Engineer role focused on building scalable healthcare data products and analytics-ready datasets for PBM and care navigation operations. The position involves developing dbt-based data models, optimizing cloud data platforms, implementing data quality frameworks, and enabling AI-assisted analytics capabilities. Candidates will collaborate cross-functionally to deliver reliable, maintainable, and auditable data solutions in a modern analytics environment. 🗂️ Requirements: 3+ years experience in analytics engineering, data modeling, data warehousing or related field, Strong experience with dbt, Advanced SQL proficiency, Experience developing data transformations and workflows using Python, Understanding of dimensional modeling and scalable data architecture, Experience building production-grade data models and data quality tests, Experience with cloud data warehouses, Experience orchestrating and monitoring data pipelines, Experience working in cloud environments, Familiarity with Git and CI/CD workflows, Knowledge of testing and deployment workflows, Strong problem-solving and analytical skills, Ability to collaborate with technical and non-technical stakeholders 📃 Skills: dbt, SQL, Python, Redshift, Snowflake, BigQuery, Airflow, Dagster, AWS, Git, CI/CD, MCP, Claude 🏢 Description: ABOUT THE ROLE: We are seeking an Analytics Engineer to join our Analytics Platform team to design, build and maintain scalable data products that power our Pharmacy Benefit Management (PBM) and Care Navigation organizations. In this role, you will be responsible for transforming complex healthcare data into trusted, analytics ready datasets that support operational reporting, client insights, financial analysis and strategic decision-making. You will partner closely with Analytics, Data Engineering, Clinical, Client Success, Product and Operations teams to build reliable and scalable data models within our data foundry. This role is ideal for someone who is passionate about analytics engineering, has strong dbt expertise, enjoys solving complex healthcare data challenges and thinks beyond individual requests to build reusable and maintainable systems. You will play a key role in shaping the future of our data platform by developing high-quality data products, establishing engineering best practices, and helping the organization evolve toward AI-enabled and self-service analytics capabilities. WHAT YOU'LL DO: • Apply hands on analytics and data expertise to solve complex, fast moving financial and operational problems in the health tech space • Design, develop and maintain scalable, analytics ready data models (primarily in dbt) that power a PBM and care navigation data ecosystem that support client reporting, performance analytics, operational analysis and self-service business intelligence • Translate complex pharmacy benefits and healthcare navigation workflows, business rules and operational processes into transparent, maintainable, and auditable data models • Partner closely with data and analytics engineers, data analysts and business stakeholders to deliver reliable data products that can be leveraged across multiple use cases and continuously optimize data models and warehouse performance to support large-scale PBM/care navigation datasets and growing business needs • Implement automated data quality checks, testing frameworks and reconciliation processes to ensure data reliability • Establish documentation standards, lineage and analytics engineering guardrails that promote transparency and auditability • Contribute to engineering best practices including version control, CI/CD, incremental models, code reviews, and observability • Contribute to data governance by establishing modeling standards, documentation and guardrails that support auditability, explainability and long term maintainability • Build data foundations that enable future agentic analytics engineering use cases, including self-service analytics and AI-assisted insight generation • Stay informed on emerging technologies and identify opportunities to incorporate AI into analytics engineering workflows WHO YOU ARE: • 3+ years of experience in analytics engineering, data modeling, data warehousing or a related field • Strong experience with dbt and modern analytics engineering best practices (required) • Advanced SQL proficiency and experience developing data transformations and workflows using python • Strong understanding of dimensional modeling, medallion architecture, semantic modeling and scalable data architecture principles • Experience building and maintaining production-grade data models, data quality tests, and documentation • Experience working with cloud data warehouses such as Amazon Redshift, Snowflake, or BigQuery • Experience orchestrating and monitoring data pipelines using tools such as Apache Airflow, Dagster etc. • Experience working within cloud environments, preferably AWS • Familiarity with software engineering practices including Git, CI/CD, pull request reviews, testing, and deployment workflows • Interest or experience in leveraging AI-enabled development workflows and analytics tooling, including experience with or willingness to learn technologies such as Claude, Claude Skills, Model Context Protocol (MCP) and AI assisted engineering practices • Strong problem-solving and analytical skills with a focus on building scalable, maintainable data solutions • Effective communication skills and the ability to collaborate with both technical and non-technical stakeholders COMPENSATION: $100,000 - $140,000 annually, in addition to bonus and equity. Compensation offered will be determined by geographic location, experience, and qualifications.

🏢 Summary: The offer is for a Data Engineer responsible for designing and developing scalable data platforms and pipelines in cloud environments, primarily on Google Cloud Platform. The role focuses on big data processing, data modeling, and building high-quality data solutions using modern distributed frameworks. The position involves working on advanced cloud-based analytics and data warehousing projects. 🗂️ Requirements: 3-4 years commercial programming experience, Experience with Google Cloud Platform, Strong knowledge of Python, Strong knowledge of SQL, Proficiency in JVM language (Scala or Java or Kotlin), Experience with BigQuery, Understanding of big data processing and storage, Experience with Apache Spark or similar framework, Experience in data modeling, Experience with CI/CD pipelines, Experience with automated testing, Experience with code review practices 📃 Skills: Python, SQL, Scala, Java, Kotlin, GCP, BigQuery, Spark, JVM, BigData, DataModeling, CICD, Testing, CodeReview 🏢 Description: We’re looking for a Data Engineer ready to push boundaries and grow with us. Datumo specializes in providing Data Engineering and Cloud Computing consulting services to clients from all over the world, primarily in Western Europe, Poland and the USA. Core industries we support include e-commerce 🛒, telecommunications 📡 and life sciences 🧬. Our team consists of exceptional people whose commitment allows us to conduct highly demanding projects. Our team members tend to stick around for more than 3 years, and when a project wraps up, we don't let them go - we embark on a journey to discover exciting new challenges for them. It's not just a workplace; it's a community that grows together! Must-have: ✅ at least 3-4 years of commercial experience in programming, ✅ proven record with a cloud provider - Google Cloud Platform, ✅ strong knowledge of Python, SQL and JVM languages (Scala or Java or Kotlin), ✅ experience in BigQuery data warehousing solution, ✅ in-depth understanding of big data aspects like data storage, modeling , processing , scheduling etc., ✅ understanding of Apache Spark (or similar distributed data processing framework), ✅ data modeling and data storage experience, ✅ ensuring solution quality through automatic tests, CI/CD and code review, ✅ proven collaboration with businesses, ✅ English proficiency at min. B2 level, proficient in Polish. Nice to have: 🌟 knowledge of dbt, Docker and Kubernetes, Apache Kafka, 🌟 familiarity with Apache Airflow or similar pipeline orchestrator, 🌟 another JVM (Java/Scala/Kotlin) programming language, 🌟 experience in Machine Learning projects, 🌟 familiarity with one of BI tools: Power BI/Looker/Tableau, 🌟 willingness to share knowledge (conferences, articles, open-source projects). What’s on offer: 🔥 100% remote work with workation opportunity (you need to be based in Poland), 🔥 20 free days, 🔥 onboarding with a dedicated mentor, 🔥 project switching possible after a certain period, 🔥 individual budget for training and conferences, 🔥 benefits: Medicover Private Medical Care , co-financing of the Medicover Sport card, 🔥 opportunity to learn English with a native speaker, 🔥 regular company trips and informal get-togethers. Development opportunities in Datumo: 🚀 participation in industry conferences, 🚀 establishing Datumo's online brand presence, 🚀 support in obtaining certifications (e.g. GCP, Azure, Snowflake), 🚀 involvement in internal initiatives, like building technological roadmaps, 🚀 training budget, 🚀 access to internal technological training repositories. Discover our exemplary project: 🔌 IoT data ingestion to cloud The project integrates data from edge devices into the cloud using Azure services. The platform supports data streaming via either the IoT Edge environment with Java or Python modules, or direct connection using Kafka protocol to Event Hubs. It also facilitates batch data transmission to ADLS. Data transformation from raw telemetry to structured tables is done through Spark jobs in Databricks or data connections and update policies in Azure Data Explorer. ☁️ Petabyte-scale data platform migration to Google Cloud The goal of the project is to improve scalability and performance of the data platform by transitioning over a thousand active pipelines to GCP. The main focus is on rearchitecting existing Spark applications to either Cloud Dataproc or Cloud BigQuery SQL, depending on the Client’s requirements and automate it using Cloud Composer. 📈 Data analytics platform for investing company The project centers on developing and overseeing a data platform for an asset management company focused on ESG investing. Databricks is the central component. The platform, built on Azure cloud, integrates various Azure services for diverse functionalities. The primary task involves implementing and extending complex ETL processes that enrich investment data, using Spark jobs in Scala. Integrations with external data providers, as well as solutions for improving data quality and optimizing cloud resources, have been implemented. 🛒 Realtime Consumer Data Platform The initiative involves constructing a consumer data platform (CDP) for a major Polish retail company. Datumo actively participates from the project’s start, contributing to planning the platform’s architecture. The CDP is built on Google Cloud Platform (GCP), utilizing services like Pub/Sub, Dataflow and BigQuery. Open-source tools, including a Kubernetes cluster with Apache Kafka, Apache Airflow and Apache Flink, are used to meet specific requirements. This combination offers significant possibilities for the platform. Recruitment process: 1️⃣Tech quiz - 15 minutes 2️⃣ Soft skills interview - 30 minutes 3️⃣ Technical interview - 60 minutes Find out more by visiting our website - https://www.datumo.io If you like what we do and you dream about creating this world with us - don’t wait, apply now!

🏢 Summary: The offer is for a Data Engineer role focused on designing, building, and optimizing scalable data platforms and pipelines in cloud environments. The position involves working with big data technologies, data warehousing solutions, and distributed processing frameworks across international projects. The role emphasizes high-quality delivery through automated testing, CI/CD, and close collaboration with business stakeholders. 🗂️ Requirements: Minimum 3 years of commercial programming experience, Experience with at least one cloud provider: GCP, Azure or AWS, Knowledge of JVM language (Scala or Java or Kotlin), Knowledge of Python, Knowledge of SQL, Experience with data warehousing solution: BigQuery or Snowflake or Databricks or similar, Understanding of big data concepts: storage, modeling, processing, scheduling, Experience in data modeling, Experience in data storage solutions, Experience with automated testing and CI/CD, Experience with code review practices, Experience in collaboration with business stakeholders, English proficiency at B2 level, Communicative Polish 📃 Skills: GCP, Azure, AWS, Scala, Java, Kotlin, Python, SQL, BigQuery, Snowflake, Databricks, Spark, Dataproc, CloudComposer, PubSub, Dataflow, Kafka, Airflow, Flink, Kubernetes, Docker, BigData, CI/CD, ETL 🏢 Description: We’re looking for a Data Engineer ready to push boundaries and grow with us. Datumo specializes in providing Data Engineering and Cloud Computing consulting services to clients from all over the world, primarily in Western Europe, Poland and the USA. Core industries we support include e-commerce 🛒, telecommunications 📡 and life sciences 🧬. Our team consists of exceptional people whose commitment allows us to conduct highly demanding projects. Our team members tend to stick around for more than 3 years, and when a project wraps up, we don't let them go - we embark on a journey to discover exciting new challenges for them. It's not just a workplace; it's a community that grows together! Must-have: ✅ at least 3 years of commercial experience in programming ✅ proven record with a selected cloud provider GCP (preferred), Azure or AWS ✅ good knowledge of JVM languages (Scala or Java or Kotlin), Python, SQL ✅ experience in one of data warehousing solutions: BigQuery/Snowflake/Databricks or similar ✅ in-depth understanding of big data aspects like data storage, modeling , processing , scheduling etc. ✅ data modeling and data storage experience ✅ ensuring solution quality through automatic tests, CI/CD and code review ✅ proven collaboration with businesses ✅ English proficiency at B2 level, communicative in Polish Nice to have: 🌟 knowledge of dbt, Docker and Kubernetes, Apache Kafka 🌟 familiarity with Apache Airflow or similar pipeline orchestrator 🌟 another JVM (Java/Scala/Kotlin) programming language 🌟 experience in Machine Learning projects 🌟 understanding of Apache Spark or similar distributed data processing framework 🌟 familiarity with one of BI tools: Power BI/Looker/Tableau 🌟 willingness to share knowledge (conferences, articles, open-source projects) What’s on offer: 🔥 100% remote work, with workation opportunity 🔥 20 free days 🔥 onboarding with a dedicated mentor 🔥 project switching possible after a certain period 🔥 individual budget for training and conferences 🔥 benefits: Medicover Private Medical Care , co-financing of the Medicover Sport card 🔥 opportunity to learn English with a native speaker 🔥 regular company trips and informal get-togethers Development opportunities in Datumo: 🚀 participation in industry conferences 🚀 establishing Datumo's online brand presence 🚀 support in obtaining certifications (e.g. GCP, Azure, Snowflake) 🚀 involvement in internal initiatives, like building technological roadmaps 🚀 training budget 🚀 access to internal technological training repositories Discover our exemplary project: 🔌 IoT data ingestion to cloud The project integrates data from edge devices into the cloud using Azure services. The platform supports data streaming via either the IoT Edge environment with Java or Python modules, or direct connection using Kafka protocol to Event Hubs. It also facilitates batch data transmission to ADLS. Data transformation from raw telemetry to structured tables is done through Spark jobs in Databricks or data connections and update policies in Azure Data Explorer. ☁️ Petabyte-scale data platform migration to Google Cloud The goal of the project is to improve scalability and performance of the data platform by transitioning over a thousand active pipelines to GCP. The main focus is on rearchitecting existing Spark applications to either Cloud Dataproc or Cloud BigQuery SQL, depending on the Client’s requirements and automate it using Cloud Composer. 📈 Data analytics platform for investing company The project centers on developing and overseeing a data platform for an asset management company focused on ESG investing. Databricks is the central component. The platform, built on Azure cloud, integrates various Azure services for diverse functionalities. The primary task involves implementing and extending complex ETL processes that enrich investment data, using Spark jobs in Scala. Integrations with external data providers, as well as solutions for improving data quality and optimizing cloud resources, have been implemented. 🛒 Realtime Consumer Data Platform The initiative involves constructing a consumer data platform (CDP) for a major Polish retail company. Datumo actively participates from the project’s start, contributing to planning the platform’s architecture. The CDP is built on Google Cloud Platform (GCP), utilizing services like Pub/Sub, Dataflow and BigQuery. Open-source tools, including a Kubernetes cluster with Apache Kafka, Apache Airflow and Apache Flink, are used to meet specific requirements. This combination offers significant possibilities for the platform. Recruitment process: 1️⃣Quiz - 15 minutes 2️⃣ Soft skills interview - 30 minutes 3️⃣ Technical interview - 60 minutes Find out more by visiting our website - https://www.datumo.io If you like what we do and you dream about creating this world with us - don’t wait, apply now!

🏢 Summary: The offer is for a Software Engineer (Data) role focused on building scalable data infrastructure and production-ready ML systems within an AI-driven environment. The position combines backend engineering, data engineering, and MLOps to design high-throughput pipelines and support AI solutions from experimentation to production. The role involves close collaboration with Data Science teams to shape architecture and engineering standards for next-generation data platforms. 🗂️ Requirements: 4+ years of software engineering experience, Strong proficiency in Python, Experience building scalable production systems, Experience with data-intensive applications and SQL databases, Knowledge of data modeling and query optimization, Experience with Terraform, Kubernetes, Docker or similar tools, Understanding of CI/CD pipelines and Infrastructure as Code, Experience implementing automated testing and clean architecture principles, Ability to productionize ML solutions with Data Science teams 📃 Skills: Python, MySQL, PostgreSQL, Spark, Terraform, Kubernetes, Docker, Airflow, SQL, CI/CD, AWS, Snowflake, DBT, MLOps 🏢 Description: Our client helps small teams power big businesses with the must-have platform for intelligent marketing automation. Customers from over 170 countries depend on the Client’s mix of pre-built automation and integration to power personalized marketing, transactional emails, and one-to-one CRM interactions throughout the customer lifecycle. We’re looking for a Software Engineer (Data) to join our client’s growing AI and Data organization and help build the scalable foundations behind next-generation data and ML systems. In this role, you won’t just be working with data infrastructure; you’ll be shaping the software architecture, engineering standards, and production-ready platforms that power the company’s AI ecosystem. This is more than a traditional backend or data engineering position. You’ll work at the intersection of software engineering, data, and AI, partnering closely with Data Science and AI teams to bridge the gap between experimentation and production. From designing resilient systems to building scalable MLOps pipelines, your work will directly influence how AI solutions are developed, deployed, and scaled across the organization. Key takeaways: Stack: Python, MySQL, PostgreSQL, Spark, Terraform, Kubernetes, Docker Salary : 20 000 - 23 000 PLN gross/month, Contract of employment (+10% annual bonus, 75% Creative Tax) Working model: Hybrid, once a week in the office Location: Krakow, ul. Konopnickiej Recruitment process: Call with MOTIFE recruiter (30 min) Interview with Hiring Manager (45 min) Technical interview, live coding (1h) Cross-functional interview (1h) Responsibilities: Design, develop, and maintain scalable high-throughput data pipelines across complex data ecosystems. Build and optimize data models, schemas, and database structures to ensure long-term scalability and performance. Implement engineering best practices, including automated testing, CI/CD pipelines, and Infrastructure as Code (Terraform). Partner closely with AI and Data Science teams to productionize machine learning solutions and develop scalable MLOps pipelines. Engineer and maintain feature stores and data infrastructure supporting AI-driven initiatives. Monitor, maintain, and improve the reliability and efficiency of containerized environments using Kubernetes, Docker, and Airflow. Ensure platform stability, observability, and operational excellence through proactive system monitoring and health checks. Collaborate cross-functionally with engineering and business stakeholders to translate complex technical concepts into actionable insights. Contribute to the architectural direction and scalability of the organization’s AI and data platforms. Drive the adoption of robust software engineering standards across data and infrastructure projects. Requirements: 4+ years of experience in software engineering, with strong hands-on experience in backend development and building scalable production systems. Strong proficiency in Python and solid software engineering fundamentals, including clean architecture, testing, and maintainable code practices. Experience working with data-intensive applications, databases, and SQL, including data modeling and query optimization. Exposure to modern data engineering, cloud, or infrastructure environments, with familiarity in tools such as Terraform, Kubernetes, Docker, or similar technologies. Understanding of CI/CD pipelines, Infrastructure as Code, and general engineering best practices. Interest in AI/ML ecosystems and willingness to work closely with Data Science and AI teams on productionizing ML solutions. Familiarity with cloud platforms and modern data stack technologies such as AWS, Snowflake, Spark, or DBT is considered a strong plus. Ownership mindset and comfort working in evolving, fast-moving environments where systems and processes are still being built. What we offer: Health Benefits 1. Medical Full coverage for employees and their dependents through LUX MED. Employees have access to the “Premium” package, providing enhanced coverage and greater access to care. A client pays 100% of the premium for employees and 50% for dependents. 2. Dental No additional cost for dental coverage- integrated into LUX MED medical plan. 3. Vision Reimbursement for vision expenses up to 400 PLN every 2 years. Mental Health Tools Access to TELUS Health EAP to provide support and resources in a time of need. Additional Benefits 10% annual bonus 75% Creative Tax Vacation: 26 days. Home Office Stipend: One-time $150 equivalent home office stipend to outfit their home office. Calm Subscription: Premium subscription access to Calm, the #1 app for sleep, meditation, and relaxation. Hub Perks: Receive meal and transportation benefits when traveling to the Poland Hub. Baby Swag: If you have a baby or adopt, you’ll receive a company-branded first bath bundle. Sabbatical Program: After 5 years of employment, receive a month-long paid sabbatical leave, with a sabbatical leave bonus.