Senior Data Engineer - Databricks

🏢 Summary: Senior Product Manager role focused on building and enhancing AI-driven CRM capabilities that improve selling workflows, productivity, and pipeline visibility. The position partners cross-functionally to deliver enterprise SaaS features across desktop and mobile experiences. The goal is to create intelligent, intuitive products that drive user adoption and measurable business impact. 🗂️ Requirements: 5+ years of product management experience, Experience delivering commercial, customer-facing software products, Proven track record shipping enterprise SaaS products, Experience in CRM, CX, or related domains, Strong understanding of user workflows and system design, Experience with data-driven product development, Bachelor’s degree in Computer Science, Engineering, Business Administration, or related field 📃 Skills: CRM, SaaS, AI, UX, Mobile, Desktop, Data, SystemDesign 🏢 Description: We’re looking for a highly skilled Senior Product Manager to define, build, and enhance key capabilities across our product portfolio. In this role, you will help shape modern selling experiences by improving CRM workflows, applying AI to increase seller productivity, and delivering insights that help managers monitor pipeline health, improve forecast accuracy, and act on risks and opportunities. You will work across desktop and mobile experiences to create intuitive, intelligent products that drive user adoption and business impact. Impact You Will Make in the Role: Design for Real-World Selling Workflows: Build intuitive CRM experiences that help sellers efficiently manage accounts, opportunities, and activities across desktop and mobile, with a strong understanding of how users actually work day to day. Apply AI to Improve Productivity: Identify opportunities to surface the right signals, recommend next-best actions, and create conversational experiences that help sellers and managers prepare, decide, and act more effectively. Enable Better Team Performance: Deliver manager-facing capabilities that provide visibility into pipeline health, improve forecast accuracy, and highlight the risks and opportunities that need attention. Drive Cross-Functional Product Execution: Partner across Engineering, UX, Architecture, and Go-To-Market teams to translate customer needs, product signals, and business priorities into clear strategy, requirements, and measurable outcomes. What You Will Bring: 5+ years of product management experience building and delivering commercial, customer-facing software products Proven success shipping enterprise SaaS products, ideally within CRM, CX, or adjacent domains Strong understanding of user workflows, system design, and data-driven product development Excellent communication, stakeholder management, and product storytelling skills Bachelor’s degree in Computer Science, Engineering, Business Administration, or related field; MBA a plus Benefits and Perks: Excellent healthcare package for you and your family Savings and Investment – 401(k) match Unlimited Paid Time Off Paid Parental Leave Online Legal Services (Rocket Lawyer) Financial Planning Services (Origin) Discounted Pet Insurance (Embrace Pet Insurance) Corporate Benefit Program (Working Advantage) with exclusive travel and entertainment offers and special discounts Health and Wellness Reimbursement Program Travel Discounts Educational Resources – Career & Personal Development Program Employee Referral Bonus Program Merit-based career growth opportunities

🏢 Summary: Hybrid Product Manager role focused on defining and delivering enterprise SaaS CRM capabilities, translating customer and business needs into actionable product requirements. The position collaborates cross-functionally with Engineering, UX, and Go-To-Market teams to drive roadmap execution, feature delivery, and data-informed product improvements. Based in Denver with a hybrid model, the role emphasizes modern workflows, user experience, and measurable product adoption. 🗂️ Requirements: 3+ years of product management experience in commercial, customer-facing software, Proven experience shipping enterprise SaaS products, Experience in CRM, CX, or related domains, Strong understanding of user workflows and system design, Experience with data-driven product development, Bachelor’s degree in Computer Science, Engineering, Business Administration, or related field, Ability to work hybrid with minimum 3 days per week in Denver office, Authorization to work in the U.S. without visa sponsorship 📃 Skills: SaaS, CRM, CX, Roadmapping, UserStories, AcceptanceCriteria, ProductAnalytics, SystemDesign 🏢 Description: About the Role We’re looking for a motivated Product Manager to help define, build, and improve key capabilities across our product portfolio. In this role, you will support the evolution of our platform to enable modern workflows, deliver intuitive user experiences, and create meaningful value for customers and the business. You’ll work closely with Engineering, UX, Architecture, and Go‑To‑Market partners to deliver features that solve real customer problems and contribute to product adoption and growth. This role operates on a hybrid model, with a mix of remote work and in-office collaboration at our Denver, CO location, specifically working in-office a minimum of 3 days per week. We are not able to offer Visa sponsorship at this time. Impact You Will Make: - Contribute to Product Roadmaps: Support the development and execution of the product roadmap for your product area, helping ensure features are aligned with customer needs, business goals, and overall product strategy. - Drive Feature Delivery: Translate customer feedback, market insights, and business requirements into clear product requirements, user stories, and acceptance criteria in collaboration with Engineering and Design. - Collaborate Across Teams: Partner with Engineering, UX, and cross‑functional stakeholders to balance customer value, usability, and technical feasibility throughout the product development lifecycle. - Learn from Data & Feedback: Help define and track success metrics such as feature usage, adoption, and customer feedback; share insights with the team to inform continuous improvement. What You Will Bring: - 3+ years of product management experience building and delivering commercial, customer‑facing software products - Proven success shipping enterprise SaaS products, ideally within CRM, CX, or adjacent domains - Strong understanding of user workflows, system design, and data‑driven product development - Excellent communication, stakeholder management, and product storytelling skills - Bachelor’s degree in Computer Science, Engineering, Business Administration, or related field Benefits and Perks: - Excellent healthcare package for you and your family - 401(k) match - Unlimited Paid Time Off - Paid Parental Leave - Online Legal Services (Rocket Lawyer) - Financial Planning Services (Origin) - Discounted Pet Insurance (Embrace Pet Insurance) - Corporate Benefit Program (Working Advantage) - Health and Wellness Reimbursement Program - Travel Discounts - Educational Resources – Career & Personal Development Program - Employee Referral Bonus Program - Merit-based career growth opportunities Our company uses E-Verify to confirm the employment eligibility of all newly hired employees.

🏢 Summary: Business Development Representative role supporting the North America sales team, focused on outbound prospecting and pipeline generation using multi-channel engagement and account intelligence. The position requires proactive outreach, relationship building with decision-makers, and qualification of opportunities for handoff to sales. This is an on-site role (4 days/week) aimed at driving measurable pipeline growth. 🗂️ Requirements: 1–2 years of value-based selling experience, Experience with outbound prospecting, Proficiency in email, social media, and video prospecting, Ability to manage and maintain pipeline in CRM, Ability to qualify leads based on established criteria, Strong written and verbal communication skills, Ability to meet monthly and quarterly prospecting targets, Comfort learning and using software applications 📃 Skills: CRM, SalesLoft, LinkedIn, ZoomInfo, Telemarketing, Email, Prospecting, Pipeline, Video, SocialMedia 🏢 Description: This posting is for future hires. This role requires on-site 4 days a week for close collaboration with the team and management. SugarAI is looking for a talented, energetic and driven individual to join the team as a Business Development Representative (BDR) in Denver. Supporting the North America sales team, you will play a pivotal role in driving outbound prospecting efforts. In this role, you will leverage account intelligence, buyer insights, and multi-channel engagement to identify, connect with, and create opportunities within strategically prioritized accounts. You will proactively engage key buyers through phone, email, video messaging, social selling, and other modern prospecting techniques to generate meaningful conversations and accelerate pipeline growth. Success in this role requires a consultative mindset, strong business acumen, and the ability to personalize outreach based on industry challenges, business initiatives, and customer needs. You will build relationships with decision-makers, uncover pain points and buying signals, and position the company’s value proposition to create qualified opportunities for the sales team. Impact You Will Make In The Role: - Proactively identify and engage with potential clients in the North America market through outbound telemarketing, email campaigns, social media outreach, and video prospecting. - Build and maintain relationships with key prospects, understanding their needs, and effectively conveying how solutions can benefit them. - Own and manage your outbound sales pipeline (from sourcing new leads, maintaining accurate records of touchpoints and statuses in the CRM, ensuring timely follow-up, to qualified hand-off). - Meet and exceed monthly and quarterly outbound prospecting and lead generation targets. - Continuously research and analyze the market to identify trends, opportunities, and potential clients. - Successfully manage and overcome prospect objections. - Stay current on products and solutions. - Actively look for opportunities to improve and optimize lead management. - Record information and maintain detailed and accurate records in the CRM system. Expertise You Will Bring: - 1–2 years of experience with value-based selling highly preferred. - Previous experience with outbound prospecting. - Strong proficiency in using email, social media platforms (LinkedIn, Twitter, etc.), and video prospecting to engage with key prospects. - Strong written and verbal communication skills. - Professional, determined, and results-oriented. - Positive attitude, team-oriented, and a self-starter. - A hunger for a career in sales and a desire to learn and grow within a dynamic sales environment. - Ability to accurately determine lead qualifications based upon established criteria. - Comfortable learning key software applications. To Stand Out from the Crowd: - Demonstrate a strong sense of accountability and goal achievement. - Thrive in a metric-driven environment, consistently track progress, and take initiative to course-correct when needed to meet or exceed performance expectations. - Previous experience using SalesLoft (or similar sales cadence tools), LinkedIn Sales Navigator and/or ZoomInfo. Benefits and Perks: - Excellent healthcare package for you and your family. - 401(k) match. - Unlimited Paid Time Off. - Paid Parental Leave. - Online Legal Services (Rocket Lawyer). - Financial Planning Services (Origin). - Discounted Pet Insurance (Embrace Pet Insurance). - Corporate Benefit Program (Working Advantage) with exclusive travel and entertainment offers and special discounts. - Health and Wellness Reimbursement Program. - Travel Discounts. - Educational Resources – Career & Personal Development Program. - Employee Referral Bonus Program. - Merit-based growth opportunities.

🏢 Summary: Senior Data Platform Engineer role focused on building and optimising a cloud-native lakehouse platform for large-scale analytics and reporting. The position involves designing distributed data pipelines, enabling self-service analytics, and implementing governance and observability frameworks using modern data technologies. You will work with Spark-based systems and integrated data warehousing solutions to deliver scalable, reliable data platforms. 🗂️ Requirements: Strong programming skills in Python, Strong programming skills in SQL, Hands-on experience with Apache Spark in production environments, Experience with Delta Lake and/or Apache Iceberg in production, Practical experience with dbt for data transformations, Experience with Databricks and Snowflake, Understanding of data governance and lineage in large-scale environments, Familiarity with Kubernetes and Docker, Experience with CI/CD and automated testing practices, Ability to participate in on-call rotations 📃 Skills: Python, SQL, Spark, Delta, Iceberg, dbt, Databricks, Snowflake, Kubernetes, Docker, CI/CD 🏢 Description: ABOUT THE COMPANY We are a global legal technology company that has been building software for the legal industry for over two decades. Our AI-powered cloud platform is used by leading law firms, Fortune 500 corporations, and government agencies worldwide to organise complex data, surface critical insights, and act on them — across litigation, investigations, regulatory inquiries, and data breach response. We're valued at $3.6 billion and invest over $170 million annually in R&D. We're making substantial investments in data lake technology and distributed systems to support future growth and advanced analytics. Our scale means the data problems here are genuinely hard — and the platforms you build will have real consequence across the organisation. ABOUT THE ROLE We're building a specialised team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. As a Senior Data Platform Engineer, you'll combine strong software engineering principles with deep data expertise to build robust, cloud-native platforms that process large-scale datasets efficiently and enable internal teams to build reporting and analytics on top of them. The role emphasises cloud-native architecture, lakehouse integration, data warehousing, and governance best practices. You'll work on systems using Apache Spark, Delta Lake, and Iceberg, and help deliver curated data models and self-service analytics capabilities to internal stakeholders. You'll also participate in on-call rotations as part of shared team responsibility. WHAT YOU'LL WORK ON Data pipeline and distributed systems Design and implement scalable data pipelines and distributed systems using Spark and Python to process and transform large-scale datasets for analytics and reporting. Lakehouse platform development Develop and maintain lakehouse capabilities with Delta Lake and Iceberg, ensuring data reliability, versioning, and performance optimisation at scale. Analytics workflow enablement Integrate dbt for SQL transformations running on Spark. Collaborate with internal teams to deliver curated datasets and self-service analytics capabilities for reporting and advanced use cases. Data warehousing optimisation Integrate and optimise Databricks and Snowflake for scalable storage and query performance. Drive performance tuning and cost optimisation across Spark jobs and cloud-native environments. Governance and observability Implement observability and governance frameworks including data lineage, quality checks, and compliance controls. Build platforms that allow secure and compliant access to diverse data sources. Engineering best practices Apply and champion clean code, modular design, CI/CD, automated testing, and code review standards across all data engineering work. On-call participation Participate in on-call rotations as part of shared team responsibility for platform reliability. WHAT WE LOOK FOR Python and SQL Strong programming skills in both Python and SQL, applied to production data platform work at scale. Apache Spark Solid hands-on experience with Spark for distributed data processing, including performance tuning in production environments. Lakehouse architecture Expertise in Delta Lake and/or Apache Iceberg. You've applied these in production and understand the trade-offs in real-world scenarios. dbt and analytics tooling Practical experience with dbt for transformation workflows. Familiarity with Databricks and Snowflake for large-scale analytics workloads. Data governance and compliance Understanding of data governance, lineage tracking, and compliance requirements in large-scale, multi-tenant data environments. Infrastructure and containerisation Familiarity with Kubernetes, Docker, and infrastructure-as-code tools in cloud-native environments. Software engineering fundamentals Solid understanding of software engineering principles — CI/CD, automated testing, clean code, and modular design applied to data systems. Bonus Exposure to event-driven architectures and advanced analytics platforms. Experience enabling self-service analytics for internal stakeholders. Experience in Java, Scala, or Rust. THE TEAM You'll join a global engineering organisation working on a platform used by some of the world's largest legal teams. The culture is diverse, inclusive, and driven by high standards. Engineers here work on genuinely complex technical problems at scale — and are supported with the coaching, development, and tooling to keep growing. COMPENSATION & BENEFITS Salary 208,000 – 312,000 PLN per year, plus an annual performance bonus and long-term incentives. Health coverage Comprehensive health, dental, and vision plans. Parental leave Parental leave available for both primary and secondary caregivers. Flexible working Flexible work arrangements with a remote-first model. Company breaks Two week-long company-wide breaks per year, plus additional time off. Training investment Dedicated training investment programme to support ongoing professional development.

🏢 Summary: Hands-on Lead Cloud Platform Engineer role focused on owning, securing, automating, and optimizing an Azure-based SaaS and AI infrastructure, including Azure Databricks and DevSecOps practices. The position covers end-to-end cloud governance, Kubernetes operations, CI/CD, security, and cost optimization in a large-scale data environment. This is a senior technical role with potential growth into technical or people leadership. 🗂️ Requirements: 7+ years in DevOps/Cloud/Platform/Infrastructure engineering, 4+ years hands-on Azure production experience, Strong Azure governance, RBAC, policies, networking, storage, monitoring, security, Experience with Entra ID and Microsoft 365 administration, Production Kubernetes experience (AKS preferred), Experience managing Azure Databricks infrastructure, CI/CD experience with Azure DevOps and/or GitHub Actions, Scripting skills (PowerShell, Azure CLI, Bash, or Python), Knowledge of cloud security principles (least privilege, secrets management, encryption, auditability), Ability to work independently and drive platform improvements 📃 Skills: Azure, Databricks, DevSecOps, AKS, Kubernetes, EntraID, Microsoft365, AzureDevOps, GitHubActions, Terraform, Bicep, ARM, PowerShell, AzureCLI, Bash, Python, ADLS, Blob, AzureSQL, KeyVault, VNets, DNS, NSG, RBAC, CI/CD, FinOps, Defender, SOC2 🏢 Description: An AI-powered consumer intelligence platform is hiring a Lead Cloud Platform Engineer (Azure, Databricks & DevSecOps). Our platform processes 50+ billion data points monthly to deliver actionable insights for leading global brands, such as Coca-Cola, Unilever, and Bayer. We run on Azure, Databricks, and GenAI workflows, and we're scaling our platform for faster delivery, stronger security, and tighter cost discipline. The Role We're hiring a hands-on cloud platform leader to own, secure, automate, and optimize our Azure-based SaaS and AI infrastructure end to end. You'll own Azure administration, Entra ID and Microsoft 365, networking, storage, Kubernetes, security, CI/CD, and FinOps, plus the cloud platform layer around Azure Databricks (networking, identity, secure access, compute governance, monitoring, and cost control). This is a hands-on role first, with a clear path to technical or people leadership as the company grows. What You'll Do • Own Azure subscriptions, governance, networking (VNets, private endpoints, DNS, NSGs), storage (ADLS Gen2, Blob), Azure SQL, Key Vault, and monitoring across all environments. • Administer Entra ID and Microsoft 365 - identities, MFA, Conditional Access, least-privilege access, and joiner/mover/leaver processes. • Manage Azure Databricks infrastructure and security: secure connectivity, networking, identity integration, compute policies, audit logging, and cost controls. • Build and improve CI/CD (Azure DevOps, GitHub Actions) and introduce Infrastructure as Code (Terraform, Bicep, or ARM) to replace manual portal changes. • Operate and secure Kubernetes/AKS environments and supporting application infrastructure. • Strengthen security and DevSecOps posture; support SOC 2 evidence, security questionnaires, and enterprise reviews. • Build monitoring, dashboards, runbooks, and incident response across the platform. • Drive Azure and Databricks cost optimization through tagging, budgets, alerts, and compute tuning. What You'll Bring: Required Qualifications • 7+ years in DevOps, Cloud, Platform, Infrastructure, or Systems Engineering, including 4+ years hands-on with Azure in production. • Strong Azure depth: subscriptions, RBAC, policies, networking, storage, monitoring, and security. • Solid experience with Entra ID and Microsoft 365 administration. • Production Kubernetes experience (AKS preferred). • Experience managing or supporting Azure Databricks infrastructure (workspace admin, compute, networking, secure storage access, identity, audit logging). • CI/CD experience with Azure DevOps and/or GitHub Actions, plus scripting (PowerShell, Azure CLI, Bash, or Python). • Strong grasp of cloud security: least privilege, secrets management, encryption, and auditability. • Proven ability to work independently, create structure, and drive improvements with minimal supervision. Nice to Have: Preferred Qualifications Experience in AI, data, analytics, or SaaS environments; Infrastructure as Code (Terraform, Bicep); SOC 2 / ISO 27001 / GDPR; Microsoft Defender for Cloud and DevSecOps tooling; FinOps and Databricks cost optimization; and working with distributed or offshore teams. What This Role Is Not This role is not a pure CI/CD role, a helpdesk-only M365 admin role, a Databricks notebook developer, a data engineering role, or a people-management role. The Opportunity • Long-term B2B contract opportunity • High Impact: We’re backed by world-class investors and work with the most iconic global consumer brands. • You’ll have ownership, with a clear path to technical or people leadership as the company grows..

🏢 Summary: Strategic Technical Product Manager (Data & AI) role owning the roadmap for customer-facing AI/ML models and data products in a SaaS environment. You will partner with executive clients to co-develop predictive features, translate business problems into technical specifications, and launch high-impact analytics solutions. This role sits at the intersection of data science, engineering, and go-to-market execution, driving measurable ARR growth. 🗂️ Requirements: 3+ years experience in Product Management, Data Analytics, or Data Engineering, Strong SQL skills (joins, aggregations), Experience with modern BI platforms (Sigma, Tableau, or Looker), Ability to translate business problems into technical data requirements, Experience working with AI/ML models or advanced analytics features, Strong understanding of SaaS product metrics and customer ROI 📃 Skills: SQL, Sigma, Tableau, Looker, Snowflake, DBT, Fivetran, Python, R, AI, ML, SaaS, Analytics, Data, Visualization 🏢 Description: We aren’t just looking for someone to manage a backlog; we’re looking for the founding architect of our customer-facing data and AI strategy. As a Technical Product Manager (Data & AI), you will sit at the intersection of Data Science, Engineering, and customer-facing value. This is a highly visible, strategic role where you’ll partner directly with executive-level clients to co-develop predictive models, analytical features, and SaaS data products. WHAT YOU'LL DO Shape the AI & Data Vision - Own the predictive roadmap for external AI/ML models, advanced analytics features, and data products - Co-innovate with strategic customers and design partners to validate ideas and uncover user needs - Partner with UX and Data Science to translate complex algorithms into intuitive data visualizations and impactful demos Execute & Ship with Impact - Translate customer business problems into technical specifications, transformation logic, and data requirements - Collaborate with Product Marketing and Sales to launch features that drive adoption, retention, and ARR expansion - Use data analysis to validate assumptions and test product hypotheses before development WHAT YOU’LL BRING - 3+ years of experience in Product Management, Data Analytics, or Data Engineering - Strong business and product acumen with ability to connect technical features to customer ROI - SQL fluency, including writing joins and aggregations - Experience with modern BI platforms such as Sigma, Tableau, or Looker - Ability to communicate effectively with executive clients, sales teams, engineers, and data scientists NICE TO HAVE - Experience with modern data stack tools such as Snowflake, DBT, Fivetran, and Sigma - Familiarity with Python or R for lightweight data analysis - Exposure to machine learning lifecycle or productionized models - Experience in complex B2B SaaS industries BENEFITS - Health and dental insurance - 401k with company match - Flexible Time Off or generous PTO plan - Paid holidays and up to 4 weeks paid bonding leave - Tuition reimbursement - Employee Assistance Program - 24/7 virtual medical care access

🏢 Summary: Senior Data Scientist role focused on building and operating real-time, AI-driven decisioning systems that directly impact user experience and conversion rates. The position involves developing and deploying production-grade machine learning models with strict low-latency requirements and contributing to personalization, experimentation, and recommendation systems. It combines hands-on ML engineering with experimentation, causal analysis, and large-scale data processing in a business-facing environment. 🗂️ Requirements: 7+ years commercial experience in Data Science with production ML focus, Strong experience deploying and maintaining production ML models, Experience with real-time systems and low-latency constraints, Proficiency in Python and SQL, Hands-on experience with gradient boosting methods, Experience with recommendation systems and uplift modeling, Strong knowledge of A/B testing and causal inference, Experience building feature engineering pipelines at scale, Experience with Apache Spark or PySpark, Cloud platform experience (AWS preferred), Familiarity with LLMs and GenAI for personalization 📃 Skills: Python, SQL, NumPy, Pandas, Scikit-learn, XGBoost, LightGBM, PySpark, Spark, AWS, Databricks, NLP, LLM, GenAI 🏢 Description: We are looking for a Senior Data Scientist to join a Growth Alliance team focused on AI-driven decisioning and user-facing machine learning systems. This role is suited for a technically strong data scientist who is equally comfortable working with business stakeholders and operating production ML systems at scale. About the Project: This is a high-impact role working directly on systems that influence end-user experience and conversion. You will operate in a real-time environment with strict low-latency requirements (<40 ms), contributing to a shift toward AI-driven decisioning aimed at improving product performance and increasing conversion rates. The work spans production ML pipelines, experimentation, and personalization, not just research or experimentation in isolation. Responsibilities: Design, develop, and deploy production machine learning models with real-time constraints; Build and maintain recommendation systems, uplift models, and contextual bandit frameworks; Conduct A/B testing, causal inference analyses, and statistical hypothesis testing; Develop and maintain feature engineering pipelines at scale using PySpark / Apache Spark; Monitor and validate deployed models to ensure performance and reliability; Collaborate closely with business stakeholders to challenge assumptions and define the right problems; Contribute to generative AI and LLM-based personalization initiatives; Work with decisioning platforms, personalization engines, and Martech integrations. Qualifications: 7+ years of commercial experience in Data Science with a strong production ML focus; Proficiency in Python (NumPy, Pandas, Scikit-learn) and SQL; Hands-on experience with gradient boosting methods (XGBoost, LightGBM); Experience with recommendation systems, clustering, NLP, and uplift modeling; Solid background in A/B testing frameworks, causal inference, and statistical modeling; Experience with feature engineering and production ML pipelines at scale; Cloud platform experience, preferably AWS; Familiarity with LLMs, prompt engineering, and GenAI for content personalization; Strong communication skills and ability to work in a highly business-facing environment; Databricks experience is a nice to have. Recruitment Process: Initial interview with our recruitment team; Interview with the hiring manager; Live Coding Assessment; Meeting with the Project Manager. Inuits Sp. z o.o. is registered in the National Register of Employment Agencies (KRAZ) under number 35420.

🏢 Summary: Design and scale high-throughput data pipelines on cloud platforms to support advanced analytics and AI-driven products. The role focuses on building distributed data architectures in AWS and Databricks, ensuring performance, governance, and data quality. You will collaborate with AI/ML teams to deliver scalable, production-grade data solutions. 🗂️ Requirements: 3+ years of data engineering experience, Strong Python programming skills, Experience with Spark or Scala, Experience building distributed data pipelines in cloud environments, Knowledge of data modeling and data warehousing principles, Bachelor’s or Master’s degree in Computer Science or Engineering 📃 Skills: Python, Spark, Scala, AWS, Glue, EMR, Fargate, StepFunctions, Databricks, SQL, APIs, GenAI, GraphDB 🏢 Description: Data Engineer – Cloud & AI Platforms We’re looking for a Data Engineer to design and scale high-throughput data pipelines supporting advanced analytics and AI-driven products. What You’ll Do Architect and maintain distributed data pipelines in Databricks and AWS (Glue, EMR, Fargate, Step Functions) Ingest and process large volumes of structured and unstructured data (internal, market, third-party, alternative sources) Collaborate with AI/ML and engineering teams to design scalable data architectures and APIs Optimize performance and cost using Spark and cloud-native best practices Implement data governance, privacy, lineage, and access controls Build automated validation, monitoring, and data quality frameworks Evaluate emerging GenAI and data tooling to enhance platform capabilities What You Bring 3+ years of experience in data engineering Strong Python and experience with Spark or Scala Proven experience building distributed pipelines in cloud environments Solid understanding of data modeling, architecture, and warehousing principles Innovative problem-solving mindset Bachelor’s or Master’s degree in Computer Science or Engineering Nice to have: Experience with graph databases.

🏢 Summary: The role focuses on designing and building scalable, cloud-native data platforms to enable advanced analytics and reporting across a large internal data ecosystem. It involves developing distributed data pipelines, lakehouse architectures, and optimised data warehousing solutions with strong emphasis on performance, governance, and reliability. The position requires deep technical expertise in big data technologies and cloud-native infrastructure, including on-call responsibility for platform stability. 🗂️ Requirements: Strong programming skills in Python, Strong programming skills in SQL, Commercial experience with Apache Spark for distributed data processing, Hands-on experience with Delta Lake and/or Apache Iceberg in production, Experience with dbt for SQL transformations, Experience with Databricks and Snowflake, Knowledge of CI/CD and automated testing practices, Experience with Kubernetes and Docker, Understanding of performance tuning and cost optimisation in large-scale data systems, Ability to participate in on-call rotations 📃 Skills: Python, SQL, Spark, Delta, Iceberg, dbt, Databricks, Snowflake, Kubernetes, Docker, CI/CD 🏢 Description: ABOUT THE COMPANY We are a global legal technology company that has been building software for the legal industry for over two decades. Our AI-powered cloud platform is used by leading law firms, Fortune 500 corporations, and government agencies worldwide to organise complex data, surface critical insights, and act on them — across litigation, investigations, regulatory inquiries, and data breach response. We're valued at $3.6 billion and invest over $170 million annually in R&D. Over 75% of our business has transitioned to our cloud platform, and we are making substantial investments in data lake technology and distributed systems to support future growth and advanced analytics. Our scale means the data problems here are genuinely hard — and the infrastructure you build will have real consequence. ABOUT THE ROLE We're building a specialised team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. As an Advanced Data Platform Engineer, you'll design and implement scalable, cloud-native data platforms that integrate modern lakehouse technologies, distributed compute frameworks, and cloud-native services to support diverse analytical use cases at enterprise scale. The role emphasises technical depth — performance optimisation, governance best practices, and the kind of engineering rigour that keeps vast datasets accessible, secure, and compliant. You'll work closely with internal teams to deliver curated datasets and self-service analytics capabilities, and you'll participate in on-call rotations as part of shared team responsibility. WHAT YOU'LL WORK ON Data pipeline and distributed systems design Design and implement complex data pipelines and distributed systems using Spark and Python, applying clean code principles, modular design, CI/CD, automated testing, and thorough code reviews. Lakehouse platform development Develop and maintain lakehouse capabilities with Delta Lake and Apache Iceberg, ensuring reliability, performance, and long-term maintainability at scale. Analytics workflow enablement Integrate dbt for SQL transformations running on Spark. Deliver curated datasets and self-service analytics capabilities that empower internal stakeholders to explore data independently. Data warehousing optimisation Optimise Databricks and Snowflake environments for performance and scalability. Drive cost optimisation and performance tuning across Spark jobs and cloud-native infrastructure. Observability and governance Implement observability and governance frameworks including data lineage tracking and compliance controls, ensuring data remains secure and auditable. On-call participation Participate in on-call rotations as part of shared team responsibility for platform reliability. WHAT WE LOOK FOR Python and SQL Strong programming skills in Python and SQL — the foundation for everything you'll build here. Apache Spark Solid experience with Spark for distributed data processing at scale, including performance tuning and optimisation. Lakehouse architecture Expertise in Delta Lake and/or Apache Iceberg. You understand the tradeoffs and have used these in production environments. Analytics tooling Familiarity with dbt, Databricks, and Snowflake for analytics workflows and SQL transformation pipelines. Software engineering fundamentals Solid understanding of software engineering principles — CI/CD, automated testing, clean code, and modular design applied to data systems. Infrastructure and containerisation Familiarity with Kubernetes, Docker, and infrastructure-as-code tools in cloud-native environments. Scalability and cost optimisation Understanding of performance tuning, scalability strategies, and cost optimisation for large-scale data systems. Bonus Exposure to event-driven architectures and advanced analytics platforms. Experience enabling self-service analytics for internal stakeholders. Experience in Java, Scala, or Rust. THE TEAM You'll join a global engineering organisation working on a platform used by some of the world's largest legal teams. The culture is diverse, inclusive, and driven by high standards. Engineers here work on genuinely complex technical problems at scale — and are supported with the coaching, development, and tooling to keep growing. COMPENSATION & BENEFITS Salary 160,000 – 240,000 PLN per year, plus an annual performance bonus and long-term incentives. Health coverage Comprehensive health, dental, and vision plans. Parental leave Parental leave available for both primary and secondary caregivers. Flexible working Flexible work arrangements with a remote-first model. Company breaks Two week-long company-wide breaks per year, plus additional time off. Training investment Dedicated training investment programme to support ongoing professional development.

🏢 Summary: Lead Data Engineer role focused on driving architecture and leading a team to build scalable, secure ETL/ELT pipelines and analytics-ready data models on modern cloud platforms. The position combines hands-on engineering with technical leadership, ensuring high standards in governance, observability, and performance optimisation. You will shape data infrastructure that supports large-scale analytics across the organisation. 🗂️ Requirements: Proven experience leading data engineering or analytics engineering teams, Strong programming skills in SQL, Strong programming skills in Python, Hands-on experience with Airflow or Prefect in production, Deep practical experience with dbt, Experience with Snowflake or Databricks at scale, Strong knowledge of dimensional modelling and SCD strategies, Experience implementing data quality and governance frameworks, Experience with CI/CD and automated testing in data systems 📃 Skills: SQL, Python, Airflow, Prefect, dbt, Snowflake, Databricks, ETL, ELT, CI/CD, SCD, Dimensional, Git, IaC 🏢 Description: ABOUT THE COMPANY Our client is a global legal technology company that has been building software for the legal industry for over two decades. Our AI-powered cloud platform is used by leading law firms, Fortune 500 corporations, and government agencies worldwide to organise complex data, surface critical insights, and act on them — across litigation, investigations, regulatory inquiries, and data breach response. We're valued at $3.6 billion and invest over $170 million annually in R&D. We're making substantial investments in data lake technology and distributed systems to support future growth and advanced analytics. Our scale means the data problems here are genuinely hard — and the infrastructure you lead will have real consequence across the organisation. ABOUT THE ROLE We're looking for a Lead Data Engineer to combine deep technical expertise with hands-on team leadership, guiding a team of data engineers building and maintaining ETL/ELT pipelines, data models, and governance frameworks that power analytics and reporting across the organisation. This is a technical leadership role — you'll drive architectural decisions, mentor engineers, and ensure delivery of secure, reliable, and scalable data solutions. You'll collaborate closely with stakeholders to align technical work with business objectives, champion governance and observability standards, and foster a culture of continuous improvement. The expectation is that you're equally effective in an architecture review as you are pairing with an engineer on a tricky pipeline problem. WHAT YOU'LL WORK ON Team leadership and mentorship Lead and mentor a team of data engineers, promoting collaboration, knowledge sharing, and professional growth. Set the standard for engineering quality and hold the bar consistently. Architecture and pipeline design Drive architectural decisions for ETL/ELT pipelines, orchestration frameworks (Airflow/Prefect), and transformation layers (dbt). Facilitate architecture reviews and contribute to design decisions for scalable, fault-tolerant systems. Analytics data modelling Oversee design and implementation of analytics-ready data models — dimensional schemas, SCD strategies, and semantic layers — that internal teams can build on reliably. Engineering best practices Ensure adherence to clean code, modular design, CI/CD, automated testing, and code review standards across all data engineering work. Platform optimisation Manage performance tuning and cost optimisation for Snowflake, Databricks, and related cloud data platforms at scale. Governance and observability Champion governance, observability, and compliance frameworks across all data workflows — including data quality, lineage tracking, and multi-tenant environment controls. Stakeholder communication Communicate effectively with leadership and cross-functional teams to provide updates, resolve blockers, and ensure timely delivery aligned with business objectives. WHAT WE LOOK FOR Proven technical team leadership Demonstrated experience leading data engineering or analytics-focused development teams — mentoring engineers, driving architectural decisions, and owning delivery outcomes. SQL and Python Strong programming skills in both SQL and Python, applied to production data systems at scale. ETL/ELT orchestration Hands-on experience with orchestration tools — Airflow and/or Prefect — in production pipeline environments. dbt expertise Deep practical experience with dbt for transformation workflows and analytics modelling, including testing, documentation, and modular project design. Snowflake and Databricks Familiarity with Snowflake and/or Databricks for large-scale data processing, including performance tuning and cost management. Data modelling principles Solid understanding of data modelling principles, incremental strategies, and schema design for analytics — dimensional modelling, SCDs, and semantic layer design. Governance and data quality Knowledge of data quality frameworks, lineage tracking, and governance in multi-tenant environments. Software engineering practices Familiarity with CI/CD, automated testing, and infrastructure-as-code practices applied to data systems. Communication and stakeholder management Strong communication skills with the ability to operate confidently across technical teams and business stakeholders. THE TEAM You'll join a global engineering organisation working on a platform used by some of the world's largest legal teams. The culture is diverse, inclusive, and driven by high standards. Engineers here work on genuinely complex technical problems at scale — and are supported with the coaching, development, and tooling to keep growing. COMPENSATION & BENEFITS Salary 270,000 – 406,000 PLN per year, plus an annual performance bonus and long-term incentives. Health coverage Comprehensive health, dental, and vision plans. Parental leave Parental leave available for both primary and secondary caregivers. Flexible working Flexible work arrangements, hybrid model. Company breaks Two week-long company-wide breaks per year, plus additional time off. Training investment Dedicated training investment programme to support ongoing professional development.