Top Data Engineer Jobs in Poland

Design, build, and maintain scalable data pipelines and warehouses for ad-tech analytics. Ingest and normalize SSP, DSP, and GAM data; develop ETL/ELT workflows, data models, quality monitoring, and privacy-compliant processing to power BI dashboards and real-time analytics.

Design, build, and operate scalable, fault-tolerant distributed data infrastructure and internal data platform products (e.g., ZooKeeper, connectors, Experimentation platform). Own end-to-end systems, improve reliability and scalability, collaborate cross-functionally, contribute to Netflix OSS, and support automated integration testing for batch and streaming connectors.

Lead migration of a large-scale analytics platform from BigQuery to Databricks. Design and implement Databricks Lakehouse architectures, build and optimize PySpark/Delta Lake pipelines, enforce governance with Unity Catalog, support production deployments, and collaborate with cross-functional teams to ensure scalable, reliable data processing and platform modernization.

Maintain and scale production data ingestion pipelines processing billions of events, support and optimize complex ETL and streaming workflows, develop platform tools and ML/streaming initiatives, ensure reliability/observability, and assist data scientists and analysts with production workloads.

As a Senior Data Engineer, you'll design and operate data pipelines on GCP, ensuring data quality, mentoring junior engineers, and supporting AI initiatives.

As a Senior Data Engineer, you'll build and manage data pipelines, ensure data quality, and collaborate across teams, contributing to the Data Platform's growth.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

Design and maintain data pipelines, ensure data reliability, structure data systems, and manage software development processes while collaborating in a team.

Design and build scalable real-time and batch data pipelines for programmatic advertising, ingesting and normalizing SSP/DSP/GAM data, maintaining warehouses, implementing ETL/ELT, ensuring data quality and privacy compliance, and supporting analytics and BI teams.

Design and build scalable real-time and batch data pipelines for programmatic ad data (bid streams, impressions, revenue). Ingest and normalize SSP/DSP/GAM data, implement ETL/ELT workflows, build and maintain data warehouses/lakes, enable auction analytics and yield optimization models, ensure data quality and privacy compliance, and support BI/analytics teams.

Build end-to-end features for a data orchestration platform across Java/Micronaut backend and Vue 3/TypeScript frontend. Implement data-aware orchestration (assets, lineage, freshness, quality), create integrations/plugins (dbt, Fivetran, Airbyte, warehouses), improve UI (flow editor, topology, dashboards), collaborate on 8-week releases, review PRs, and engage with the open-source community.

Develop software for risk data pipelines, collaborating with trading teams to manage trade data, improve capital efficiency, and automate operations.

The Senior Data Engineer will design and evolve the internal Data Platform, focusing on architecture, data engineering, and mentoring while ensuring standards for data quality and governance.

Develop and maintain a cloud-native data ecosystem focusing on metadata management and data quality, integrating solutions with analytical tools, and collaborating with various teams.

Build and maintain high-throughput data pipelines, design schemas and data models, implement IaC and CI/CD, collaborate with Data Science/AI on feature stores and MLOps, monitor containerized systems, and advise stakeholders on data architecture.

Design and build highly scalable, low-latency market data systems and APIs. Implement backend services, influence architecture, maintain test coverage, participate in code reviews, troubleshoot incidents, and occasionally be on-call. Work spans streaming and historical market data endpoints and developer-focused API improvements.

Develop and enhance BI solutions using SAP technologies, ensuring best practices in performance, data integration, and training users on SAP Data & Analytics.

Design and build reusable Databricks Lakehouse PySpark pipelines, implement data models (fact/dimension, SCD Type 2), enable incremental/idempotent loads, optimize performance, implement event-driven integrations, collaborate on Azure cloud resources, and improve data platform architecture.

Design, develop, and maintain data-driven solutions for regulatory and product stewardship applications. Translate business requirements into scalable implementations, write and optimize SQL, troubleshoot data issues, collaborate with cross-functional teams, and support large-scale regulatory data products through planning, testing, and deployment.

Design, build, and operate Azure-based data platform environments and lead migrations to Azure/Databricks/Microsoft Fabric. Implement IaC (Terraform), Kubernetes platform operations, CI/CD automation, security and governance controls, monitoring/observability, and cost/performance optimizations. Collaborate with data engineers, architects, and stakeholders and produce technical documentation while providing technical leadership during the migration.

Design, build, and maintain data platform tooling and developer self-service capabilities. Build CLI tools, Data Product templates, Airflow components, Terraform/IaC assets, GitOps integrations, telemetry, and Agentic AI workflows while collaborating with platform, data engineering, analytics, and ML teams.

Design and implement scalable cloud data infrastructure, ETL pipelines, data models, and warehouses. Develop data processing solutions in Python and SQL, integrate legacy and modern systems, prepare data for AI use cases, gather requirements, produce technical specifications, scope releases, manage code reviews, and liaise with customers.

Own and operate Databricks-based data platform production support, build and migrate ETL/ELT pipelines to Databricks across Azure/AWS, optimize compute and performance, enforce Delta Lake architecture and data security, implement observability and CI/CD, support multi-tenant onboarding and on-call incident response, and maintain runbooks and SLA metrics.

Design, build, and maintain analytics-ready datasets and ETL for cybersecurity reporting; develop scripts and dashboards for tools like CrowdStrike, Prisma/Cortex, and MS InTune; create Power BI on-demand and static reports; translate security objectives into measurable metrics and present to technology leaders.

Lead technical design and delivery of enterprise-scale data platform capabilities (ingestion, ETL/ELT, governance, observability). Influence architecture and standards across squads, mentor engineers, drive scalability, performance, CI/CD, and platform reliability in a cloud (Azure) environment to enable analytics and AI use cases.