Associate Client Data Engineer

🏢 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: Senior Data Engineer role focused on designing and building scalable serverless data ingestion pipelines in AWS within the healthcare domain. The position emphasizes strong Python engineering, cloud architecture leadership, and implementation of modern data platforms and DevOps practices. The role involves driving technical excellence and delivering reliable, high-impact data solutions in an international environment. 🗂️ Requirements: 10+ years of experience in Python programming, Strong software engineering skills in data processing, Extensive experience with AWS Cloud and Serverless Architecture, Hands-on experience with AWS Lambda, S3, and Cognito, Experience building E2E automated tests for data pipelines, Practical knowledge of Data Mesh and Medallion Architecture, Experience with Infrastructure as Code using AWS CDK or Terraform, Experience with CI/CD pipelines using GitLab or GitHub Actions, Experience with ETL/ELT processes and dbt, Experience working with GraphQL, Minimum B2 level English proficiency 📃 Skills: Python, AWS, Lambda, S3, Cognito, Boto3, DataMesh, Medallion, CDK, Terraform, GitLab, GitHubActions, ETL, ELT, dbt, GraphQL, CI/CD 🏢 Description: We are looking for a highly skilled Data Engineer to join our client in the healthcare sector. Our requirements: Technical Expertise: Python Programming: 10+ years of experience with strong Software Engineering skills focused on data processing. AWS & Serverless: Extensive experience with AWS Cloud, specifically focusing on Serverless Architecture and services (including AWS Lambda , AWS S3 Tables , and AWS Cognito ). Automated Testing: Proven experience in developing End-to-End (E2E) automated tests to ensure pipeline reliability, utilizing tools such as Boto3 for AWS resource validation. Data Concepts: Practical knowledge of Data Mesh and Medallion Architecture , along with general data processing and analysis. DevOps & IaC: Hands-on experience with Infrastructure as Code ( AWS CDK or Terraform ) and CI/CD pipelines ( GitLab pipelines or GitHub Actions ). Modern Tooling: Experience with ETL/ELT solutions, dbt , and GraphQL . Communication & Soft Skills: English Language: Minimum B2 level , enabling smooth daily technical and business communication in a global environment. Collaboration: Excellent communication skills and the ability to thrive in a collaborative, international team. Standards: A strong commitment to high standards of ethics, quality (Clean Code), and reliable delivery. Nice to have: Experience with Snowflake and SQL . Knowledge of Data Vault 2.0 modeling. Experience with Databricks . Familiarity with the Microsoft ecosystem: C# / .Net, T-SQL, SQL Server , and Azure DevOps . Experience with Star Schema database modeling. Knowledge of Descriptive Statistics. Your responsibilites: Design and build scalable Data Ingestion pipelines within the AWS cloud ecosystem. Lead technical delivery and implementation of core platform components, ensuring architectural integrity across the entire data lifecycle. Collaborate with Engineering Managers and cross-functional teams across the globe and Poland. Drive technical excellence by improving team processes, architecture standards, and engineering best practices. Support and consult with stakeholders to ensure successful delivery of high-impact, data-driven solutions. Contribute to the growth and maturity of the team’s cloud and data engineering capabilities. We offer: Challenging role within the company that creates innovative solutions. Work in international environment on demanding projects. Remote work model. Subsidized private medical care, life insurance, multisport card. Integration meetings. Employee referral program. If you have a deep expertise in Python and AWS , and building scalable Serverless data architectures is where you truly excel, this is the perfect role for you!

🏢 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: Lead Data Engineer role focused on driving AI initiatives and building scalable cloud-based data architectures in a global environment. The position involves technical ownership of data platforms, designing secure and high-performing systems, and leading data engineering efforts in a DevOps setting. The role emphasizes AI integration, cloud infrastructure, and enterprise-grade data governance. 🗂️ Requirements: Degree in Computer Science, AI, Data Science, Software Engineering or equivalent experience, 8+ years in software engineering, 5+ years of backend development with Python in production, Strong experience designing and scaling complex data systems, Hands-on experience with AI technologies, Hands-on experience with AWS or Azure, Strong knowledge of Python and SQL, Experience with APIs and data integration, Experience with automation tools, Knowledge of data governance practices, Understanding of data security and compliance standards, Proven experience leading and mentoring engineers 📃 Skills: Python, SQL, AWS, Azure, Java, AI, RAG, MCP, APIs, DevOps, Automation, Monitoring, Cloud, DataEngineering, DataPipelines, Governance, Security, Compliance, Backend 🏢 Description: We are looking for an experienced Lead Data Engineer to drive AI and cloud-based data solutions within a global technology organization. In this role, you will lead data initiatives, shape scalable architectures, and collaborate with both technical teams and senior stakeholders to deliver secure and high-performing systems. Key Responsibilities: Act as the main point of contact for data access and system-related topics with senior stakeholders Lead and mentor data engineers, promoting best practices and technical excellence Design, build, and maintain scalable cloud infrastructure and data pipelines Ensure data quality, security, compliance, and governance across the full lifecycle Develop secure and reliable cloud architectures (AWS/Azure) for AI and enterprise applications Implement monitoring, alerting, disaster recovery, and business continuity solutions Take technical ownership of applications within a DevOps environment Drive automation and self-service capabilities Support AI initiatives (e.g., AI Agents, RAG, MCP) with focus on quality and scalability Stay updated on emerging technologies and advise on strategic data direction Requirements: Degree in Computer Science, AI, Data Science, Software Engineering, or equivalent experience 8+ years in software engineering, including 5+ years of backend development with Python (production level) Strong experience designing and scaling complex data systems Hands-on experience with AI technologies and cloud platforms (AWS or Azure) Solid knowledge of Python, SQL (Java is a plus) Experience with APIs, data integration, automation tools, and data governance Strong understanding of data security and compliance standards Proven leadership and mentoring experience Excellent communication skills in English and Polish (min. B2); German is a plus What We Offer: Opportunity to work in a global, international environment Real impact on AI and cloud solutions in a large-scale organization Access to training platforms and professional development programs Hybrid work model with flexible hours (modern office in central Wroclaw) Comprehensive benefits package (medical & dental care, sports card, life insurance, mental health program) Cafeteria benefits platform with monthly points CSR initiatives, integration events, and employee passion clubs

🏢 Summary: Lead Data Engineer role focused on building scalable AI and cloud-based data solutions in a global environment. The position involves leading data engineering initiatives, designing secure cloud architectures, and supporting AI applications using AWS or Azure. The offer includes hybrid work, professional development opportunities, and a comprehensive benefits package. 🗂️ Requirements: Degree in Computer Science, AI, Data Science, Software Engineering, or equivalent experience, 8+ years in software engineering, 5+ years of backend development with Python, Experience designing and scaling complex data systems, Hands-on experience with AI technologies, Experience with AWS or Azure, Strong knowledge of Python and SQL, Experience with APIs, data integration, automation tools, and data governance, Understanding of data security and compliance standards, Leadership and mentoring experience, English and Polish proficiency (minimum B2) 📃 Skills: Python, SQL, AWS, Azure, Java, APIs, DevOps, AI, RAG, MCP, Automation, DataGovernance 🏢 Description: We are looking for an experienced Lead Data Engineer to drive AI and cloud-based data solutions within a global technology organization. In this role, you will lead data initiatives, shape scalable architectures, and collaborate with both technical teams and senior stakeholders to deliver secure and high-performing systems. Key Responsibilities: Act as the main point of contact for data access and system-related topics with senior stakeholders Lead and mentor data engineers, promoting best practices and technical excellence Design, build, and maintain scalable cloud infrastructure and data pipelines Ensure data quality, security, compliance, and governance across the full lifecycle Develop secure and reliable cloud architectures (AWS/Azure) for AI and enterprise applications Implement monitoring, alerting, disaster recovery, and business continuity solutions Take technical ownership of applications within a DevOps environment Drive automation and self-service capabilities Support AI initiatives (e.g., AI Agents, RAG, MCP) with focus on quality and scalability Stay updated on emerging technologies and advise on strategic data direction Requirements: Degree in Computer Science, AI, Data Science, Software Engineering, or equivalent experience 8+ years in software engineering, including 5+ years of backend development with Python (production level) Strong experience designing and scaling complex data systems Hands-on experience with AI technologies and cloud platforms (AWS or Azure) Solid knowledge of Python, SQL (Java is a plus) Experience with APIs, data integration, automation tools, and data governance Strong understanding of data security and compliance standards Proven leadership and mentoring experience Excellent communication skills in English and Polish (min. B2); German is a plus What We Offer: Opportunity to work in a global, international environment Real impact on AI and cloud solutions in a large-scale organization Access to training platforms and professional development programs Hybrid work model with flexible hours (modern office in central Wroclaw) Comprehensive benefits package (medical & dental care, sports card, life insurance, mental health program) Cafeteria benefits platform with monthly points CSR initiatives, integration events, and employee passion clubs

🏢 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: Senior hands-on Staff Data Engineer role focused on owning and scaling a centralized Databricks lakehouse platform, building production-grade data pipelines, and leading multi-terabyte legacy migrations. The position combines architectural decision-making, data modeling, and technical leadership to support multiple financial product lines. The engineer acts as the primary onshore technical authority ensuring platform reliability, governance, and scalability. 🗂️ Requirements: 5+ years of data engineering experience, Strong proficiency in SQL, Python, and PySpark, Hands-on experience with Databricks (Delta Lake, Workflows, Databricks SQL), Experience building and maintaining large-scale ETL/ELT pipelines, Proven ability to design scalable data models, Experience migrating multi-terabyte datasets, AWS experience (S3, IAM, VPC), Infrastructure-as-code experience (Terraform preferred), Knowledge of data governance, lineage, and access controls, Ability to make independent architectural decisions, Experience mentoring data engineers, US-based with timezone overlap for stakeholder collaboration 📃 Skills: SQL, Python, PySpark, Databricks, Delta, Lake, Workflows, DatabricksSQL, UnityCatalog, AWS, S3, IAM, VPC, Terraform, ETL, ELT, DataModeling, Governance 🏢 Description: Exactera has offices in New York City, Tarrytown NY, San Diego, CA, London, and Argentina. The Role As Staff Data Engineer, you will provide senior onshore technical leadership for the data engineering team. You will own a defined slice of our centralized Databricks data platform with full accountability for decisions and delivery, serve as a technical counterpart to the Principal Data Platform Engineer, and drive architectural judgment and independent problem-solving as platform complexity scales post-migration. This is a hands-on data engineering role focused on building and maintaining production pipelines, exercising architectural judgment on data modeling and pipeline design, and serving as the onshore escalation point and institutional knowledge backup for platform decisions. The Business Challenge We operate multiple product lines (Transfer Pricing, R&D Services, RoyaltyStat, Provisioning), each with distinct databases containing enterprise financial data—journal entries, general ledgers, and financial statements. Our immediate challenge is migrating multi-terabyte datasets from legacy systems to a unified Databricks lakehouse while establishing governance patterns that enable multi-product operations at scale. As the platform matures, the data engineering team needs senior onshore technical presence to drive architecture ownership and maintain platform quality. What You'll Build Production Data Pipelines: Build and maintain production data pipelines within the patterns and governance established by the Lead Data Platform Engineer, ensuring reliability and performance at multi-terabyte scale. Data Modeling & Architecture: Exercise architectural judgment on data modeling, pipeline design, and platform usage—translating complex business requirements into scalable data solutions across our product portfolio. Stakeholder Engagement: Engage proactively with product and engineering stakeholders to translate requirements into data solutions, serving as the primary onshore technical point of contact for data engineering needs. Platform Quality: Drive platform quality through code reviews, testing practices, and engineering standards that ensure the team delivers reliable, maintainable data infrastructure. Knowledge & Continuity: Serve as onshore escalation point and institutional knowledge backup for platform decisions, reducing single-point-of-failure risk and building onshore technical depth as the platform scales. Business Problems You'll Solve Multi-Product Data Delivery: Implement data pipelines that serve multiple product lines (Transfer Pricing, R&D Services, RoyaltyStat, Provisioning) with distinct data requirements, ensuring each product gets the data it needs reliably and on schedule. Legacy Migration Execution: Lead pipeline implementation for migrating multi-terabyte datasets from legacy systems to Databricks, working within the architecture defined by the Lead Data Platform Engineer. Onshore Technical Leadership: Provide the senior judgment layer the current nearshore team cannot—owning problems end-to-end, making independent architectural decisions, and mentoring engineers to raise the quality bar across the team. Cross-Team Coordination: Bridge the gap between product teams and data infrastructure, translating business requirements into data solutions and ensuring the data platform delivers on product commitments. Required Experience Core Data Engineering SQL, Python, and PySpark—production pipeline implementation and performance optimization Databricks experience—Delta Lake, Workflows, and Databricks SQL; Unity Catalog familiarity preferred 5+ years in data engineering with demonstrated ability to own problems end-to-end without close direction Experience building and maintaining ETL/ELT pipelines at scale, including error handling, monitoring, and data quality validation Strong data modeling skills across structured and semi-structured data sources Platform & Infrastructure AWS experience (S3, IAM, VPC) with ability to collaborate on infrastructure decisions Infrastructure-as-code experience (Terraform preferred) Familiarity with data governance patterns (Unity Catalog, data lineage, access controls) Technical Leadership Demonstrated ability to exercise independent architectural judgment—not just ticket execution Experience mentoring or guiding junior and mid-level data engineers Strong written and verbal communication—able to document architecture decisions and engage directly with both technical and business stakeholders Onshore (US-based)—role requires timezone overlap, async-light communication, and direct stakeholder engagement Preferred But Not Required Experience with financial data, accounting systems (NetSuite), or enterprise ERP platforms Background building pipelines that serve AI/ML workloads (preparing data for downstream ML consumption, RAG, and LLMs) Familiarity with data governance frameworks and compliance requirements for regulated industries Experience working alongside or transitioning from nearshore engineering teams What We Offer (The following only applies to US-based positions) A collaborative team culture with opportunities for career development. Ample opportunities to be recognized, build valuable skills, and grow your career. Generous vacation policy, including paid parental leave. Comprehensive health plans with FSA and HSA options. 401(k) retirement plan. Life and disability insurance coverage. Supplemental benefits like a dependent care savings plan, pet insurance, will preparation, and an employee assistance program. About Us At Exactera, a FinTech SaaS start-up founded in 2016, we stand at the intersection of human and machine intelligence. Our corporate tax solutions are powered by AI and cloud-based technologies, serving customers worldwide. We are committed to diversity, inclusion, and equal opportunities for all. What We Offer:(The following only applies to US-based positions) A collaborative team culture with opportunities for career development. Ample opportunities to be recognized, build valuable skills, and grow your career. Generous vacation policy, including paid parental leave. Comprehensive health plans with FSA and HSA options. 401(k) retirement plan. Life and disability insurance coverage. Supplemental benefits like a dependent care savings plan, pet insurance, will preparation, and an employee assistance program. About Us: At Exactera, a FinTech SaaS start-up founded in 2016, we stand at the intersection of human and machine intelligence. Our corporate tax solutions are powered by AI and cloud-based technologies, serving customers worldwide. With over $100 million in funding from Savant Venture Fund and Insight Partners, we are poised for growth. We are committed to diversity, inclusion, and equal opportunities for all.

🏢 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: Engineering Manager role leading a client-facing team responsible for delivery and site operations of a financial services web platform, with a strong focus on AI-augmented workflows and engineering excellence. The position combines technical leadership, SRE practices, and modernization of development processes through automation and AI tooling. This is a hybrid role requiring collaboration with cross-functional teams and direct client engagement. 🗂️ Requirements: 3+ years of engineering management experience, Experience managing and mentoring software engineers, Proficiency in JavaScript/TypeScript, HTML/CSS, React, Node.js, Understanding of web application architecture (client-server, RESTful services, microservices), Experience with code reviews and testing strategies (unit, integration, end-to-end), Experience with Agile/Scrum methodologies, Familiarity with CI/CD pipelines and deployment tooling, Experience with AI-assisted development tools, Familiarity with agentic workflows or automation frameworks, Understanding of web analytics tools, Familiarity with SQL and NoSQL databases, Knowledge of WCAG accessibility standards, Familiarity with SOC2 processes and controls, Understanding of OWASP guidelines and data protection regulations 📃 Skills: JavaScript, TypeScript, HTML, CSS, React, Node.js, REST, Microservices, CI/CD, Harness, GitHub, GitHubActions, Copilot, Cursor, Claude, SQL, NoSQL, GoogleAnalytics, Mixpanel, WCAG, SOC2, OWASP, GDPR, CCPA, Agile, Scrum 🏢 Description: This role is not open to visa sponsorship or transfer of visa sponsorship including those on H1-B, F-1, OPT, STEM-OPT, or TN visa, nor is it available to work corp-to-corp. This role requires a hybrid schedule and will be based in our South Charlotte, NC or New York, NY office (Tuesday through Thursday) and optional remote days on Mondays and Fridays each week. Red Ventures Growth and Transformation partners with financial institutions to build digital products, customer platforms, and marketing technology solutions that drive acquisition, deepening, and retention. Red Ventures is looking for a technically strong, growth-minded Engineering Manager to lead a client-facing engineering team within our Banking Client Services organization. You’ll own the engineering delivery and site operations for a financial services’ web presence, leading a small team today with a clear path to growth as the client partnership expands. What sets this role apart: you’ll operate at the intersection of client-facing engineering leadership and modern AI-augmented workflows. Our teams are actively integrating agentic tooling and automation into how we code, manage tickets, maintain compliance, and solve problems alongside our business and data science partners. We’re looking for someone who is energized by this shift and ready to lead a team through it. This role reports to the Director of Engineering and will serve as the technical lead on client engagements when needed, with the Director’s support. The ideal candidate has strong communication instincts and the desire to grow into an increasingly senior client-facing leadership role over time. Travel to partner locations is an expected component of this role to support relationship management and business objectives. Curious how Growth and Transformation fits into Red Ventures? Click here. What You’ll Do: Team & Client Leadership Lead a team of software engineers responsible for the engineering delivery and site operations of a financial services web platform. Serve as the technical lead on client calls and escalations, communicating complex technical topics clearly to both technical and non-technical stakeholders. Collaborate with designers, customer experience leads, business stakeholders, and leadership to deliver high-quality solutions that strengthen client trust. Position engineers for success through coaching, mentorship, regular feedback, and personal development planning. AI & Process Modernization Champion the adoption and effective use of agentic workflows and AI-assisted tooling for coding, ticket management, compliance, and engineering process improvement. Leverage internally-built automation and AI tooling to increase team efficiency, reduce manual toil, and improve delivery quality. Partner with business and data science teams to identify and implement AI-driven solutions to operational and client-facing problems. Stay current with emerging AI/ML tooling for software development (IDE integrations, CLI agents, code review automation) and evaluate their fit for the team. Site Operations & Engineering Excellence Drive SRE best practices: observability, incident response, reliability, and operational maturity for client-facing web properties. Improve engineering processes, CI/CD pipelines, code quality, and testing practices across the team. Demonstrate project and roadmap planning skills, balancing client commitments with operational health and team investment. What We’re Looking For: Leadership & Communication Experience managing and mentoring software engineers, including coaching, delivering feedback, and supporting career growth. Strong verbal and written communication skills with the ability to translate technical concepts for non-technical audiences, including client stakeholders. Skills in managing team dynamics, navigating conflict constructively, and building a collaborative, psychologically safe environment. Experience collaborating across functions: design, marketing, data science, and business partners to align on priorities and deliver outcomes. Comfort operating as a technical lead on client-facing calls and escalations with leadership support. 3+ years of engineering management experience Software Engineering Proficiency in web development languages and frameworks (e.g., JavaScript/TypeScript, HTML/CSS, React, Node.js). Understanding of web application architecture: client-server models, RESTful services, and microservices. Strong emphasis on code quality: code reviews, testing strategies (unit, integration, end-to-end), and engineering best practices. Experience with Agile/Scrum methodologies and managing delivery through sprints and iterative planning. Familiarity with CI/CD pipelines and deployment tooling (e.g., Harness, GitHub Actions). AI Fluency & Automation Mindset Demonstrated comfort with AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude, or similar IDE/CLI integrations). Familiarity with agentic workflows or automation frameworks used to streamline engineering, compliance, or operational processes. A proactive mindset toward identifying opportunities to apply AI and automation to reduce toil and improve outcomes. Willingness to experiment, evaluate new tooling, and lead a team through adoption of emerging AI capabilities. Data, Accessibility & Security Understanding of web analytics tools (e.g., Google Analytics, Mixpanel) and the ability to use data to inform engineering decisions. Familiarity with databases (SQL and NoSQL) and their integration with web applications. Knowledge of WCAG accessibility standards and experience implementing accessibility testing practices. Familiarity with process and controls required in SOC2 operations. Demonstrated experience leading in SOC2 environments preferred. Understanding of web security principles (OWASP guidelines) and data handling regulations (e.g., GDPR, CCPA), particularly important in a financial services context. Compensation: This range reflects total cash compensation, which may include base salary only or base salary plus target bonus, depending on the role. Where eligible, equity may also be offered separately and not included below. Actual compensation varies based on location, experience, and qualifications. Total Cash Compensation Range Charlotte, NC Hybrid Compensation Range: $130,000 - $210,000 per year New York, NY Hybrid Compensation Range: $162,500- $262,500 per year Additionally, the following benefits are provided by Red Ventures, subject to eligibility requirements. Health Insurance Coverage (medical, dental, and vision) Life Insurance Short and Long-Term Disability Insurance Flexible Spending Accounts Holiday Pay 401(k) with match Employee Assistance Program Paid Parental Bonding Benefit Program Flexible Paid Time Off (PTO): We believe time to rest and recharge is essential. That’s why we offer a generous and flexible PTO policy. Full-time employees accrue 20 days of PTO for a full calendar year annually, with an increase to 25 days after five years of service. Who We Are: Red Ventures is a global portfolio of high-growth companies — spanning several U.S. businesses, a joint venture in the health services industry, and strategic investments in Europe. Their businesses include The Points Guy, Lonely Planet, Bankrate, the Allconnect Platform, RV Home Client Growth, RV Growth & Transformation, Sage Home Loans Corporation, and more. Across the portfolio, Red Ventures businesses deliver seamless digital experiences for consumers, help Fortune 100 clients solve large-scale digital growth challenges, and create world-class experiences and opportunities for employees. Learn more at redventures.com and follow @RedVentures on LinkedIn and Instagram. At Red Ventures, we believe diverse, inclusive teams are better. To help you better understand our core values and beliefs, we encourage you to watch this brief YouTube video: Our Belief Statements. This will give you insight into the principles that guide our work and our commitment to fostering an inclusive environment. We offer competitive salaries and a comprehensive benefits program for full-time employees, including medical, dental and vision coverage, paid time off, life insurance, disability coverage, employee assistance program, 401(k) plan and a paid parental leave program. Red Ventures is an equal opportunity employer that does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or any other basis protected by law. Employment at Red Ventures is based solely on a person's merit and qualifications. We are committed to providing equal employment opportunities to qualified individuals with disabilities. This includes providing reasonable accommodation where appropriate. Should you require a reasonable accommodation to apply or participate in the job application or interview process, please contact accommodation@redventures.com. If you are based in California, we encourage you to read this important information for California residents linked here. #LI-KS1 #LI-HYBRIDClick here for more details regarding the employee privacy policy: https://www.redventures.com/legal/us-emp-privacy-notice Questions about this Privacy Notice can be directed to employeerights@redventures.com. Alternatively, you may raise any questions or concerns to your manager, HR Business Partner, or through the Privacy Team.

🏢 Summary: Design and build a modern Data Platform from scratch for an insurance client, establishing a governed, production-ready Snowflake environment and enabling AI capabilities. The role covers full lifecycle ownership from architecture and data modelling to pipeline implementation and post-launch operations. You will develop scalable data ingestion and processing solutions while promoting best practices, automation, and CI/CD standards. 🗂️ Requirements: Hands-on experience with Python, Proven experience with data warehouse solutions (Snowflake, BigQuery or Redshift), Experience with Databricks or data lakehouse platforms, Strong expertise in data modelling and ETL/pipeline design, Experience with cloud platforms (AWS, GCP or Azure), Experience with cloud data services (S3, GCS, ABS, EMR, Dataproc, MWAA, Composer, ADF or AWS Glue), Ability to design and maintain data quality and governance standards, Experience working in Agile environments 📃 Skills: Python, SQL, Snowflake, Databricks, BigQuery, Redshift, Azure, AWS, GCP, Terraform, dbt, Spark, PowerBI, ADF, Glue, EMR, Dataproc, MWAA, Composer 🏢 Description: We are #VLteam – tech enthusiasts constantly striving for growth. The team is our foundation, that’s why we care the most about the friendly atmosphere, a lot of self-development opportunities and good working conditions. Trust and autonomy are two essential qualities that drive our performance. We simply believe in the idea of ​​“measuring outcomes, not hours”. Join us & see for yourself! About the role The majority of these roles will be at the forefront of client collaboration and building VL positions in the industry (spearheading projects). You will work closely and directly with a different specialist from the client side. Collaborate with stakeholders to define requirements, develop data pipelines and data quality metrics. You will participate in defining the requirements and architecture for the new platform, implement the solution, and remain involved in its operations and maintenance post-launch Your work will also introduce data governance and management, laying the foundation for accurate and comprehensive reporting that was previously impossible. Build data ingestion & processing pipelines. All of the above with a strong focus on the customer’s needs. Flexibility in action and the ability to overcome obstacles are highly valued in this role. View available projects: Project JetBrains Projectt scope The client is introducing Atlan as a new internal Data Catalogue solution and uses Glean as a company-wide unified search platform for thousands of employees. To ensure a smooth transition from our existing Knowledge Base and OpenMetadata setup, we need to index Atlan assets into Glean so that metadata for databases, tables, metrics, and reports is easily discoverable through search. Tech stack Python,  System & Data Integration, Kubernetes, System design, Infrastructure mindset Skills We’re looking for a Data Platform Engineer with experience in data platforms and system design at scale. We expect a track record in designing integration architectures for external systems and streamlining data migration/ingestion. As a Data Platform Engineer, you will design and implement a solution that: Periodically indexes Atlan metadata assets into Glean, runs on a configurable schedule (hourly/daily), is production-ready, observable, and maintainable by our DevOps team after handover. Moreover, ensure compliance and data governance at the appropriate level in line with the company’s standards. What we expect in general A proactive approach and flexibility in action were a must Very good command of English (written and spoken) Hands-on experience with Python Proven experience with data warehouse solutions (e.g., BigQuery, Redshift, Snowflake) Experience with Databricks or data lakehouse platforms Strong background in data modelling, data catalogue concepts, data formats, and data pipelines/ETL design, implementation and maintenance Ability to thrive in an Agile environment, collaborating with team members to solve complex problems with transparency Experience with AWS/GCP/Azure cloud services, including: GCS/S3/ABS, EMR/Dataproc, MWAA/Composer or Microsoft Fabric, ADF/AWS Glue Experience in ecosystems requiring improvements and the drive to implement best practices as a long-term process Experience with Infrastructure as Code practices, particularly Terraform, is an advantage Proactive approach Don’t worry if you don’t meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more! Apply now