Top Data Engineer Jobs in Poland

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.

Analyze user behavior on websites and apps, focusing on KPIs and data visualization. Build dashboards, run A/B tests, and communicate findings to stakeholders.

Owner of all PostgreSQL databases underpinning a multi-site telecom platform. Responsibilities include DB installation, HA, backup/restore, performance tuning, large-scale bulk loads/migrations, multi-datacenter replication, data governance (retention, masking, archival), monitoring (Prometheus/Grafana), automation scripting, and cross-platform integration with network-element databases.

The role involves creating and automating infrastructure features for data platforms using Python, with a focus on distributed systems and collaboration within a global team.

The role involves automating OpenSearch operations by developing features in Python, collaborating with an international team, and providing expertise on data platforms.

As a Software Engineer on the data platform team, you'll automate data platform operations, write Python code, and collaborate on solutions within a distributed team.

Leads the design and development of enterprise data warehouses, lakes, and governed data platforms. Builds scalable batch and real-time ETL/ELT pipelines using Databricks, SQL, Python, and PySpark; drives legacy migration and enterprise data integration. Enables analytics, automation, and AI use cases while establishing engineering standards, mentoring technical teams, and partnering with stakeholders on strategic data transformation initiatives.

Join Zencore as a Senior Data Engineer, leveraging Google Cloud expertise and technology strategies to assist clients with data and application modernization.

Design and scale mission-critical market data services for stocks, options, crypto, and foreign exchange. Responsibilities include architecting backend systems and APIs, maintaining software quality and test coverage, participating in code reviews, and troubleshooting incidents and bugs. The role uses Go and Python with REST, gRPC, WebSockets, SSE, Docker, Kubernetes, Google Cloud, BigTable, Prometheus, Grafana, and ELK.

Lead design and delivery of end-to-end ML/AI solutions: architect systems, implement and validate models, oversee data pipelines, coordinate cross-functional teams, mentor engineers, liaise with clients, and ensure timely Agile delivery.

The Senior Data Engineer will design and build data pipelines on GCP, ensuring high data quality and reliability for analytics and ML products. Responsibilities include mastering ETL processes, managing workflows with Airflow, and collaborating closely with ML engineers.

The Senior Data Engineer will own end-to-end data pipeline work, maintain production pipelines, integrate new data sources, and collaborate with data scientists.

Design, build, and maintain scalable Databricks ETL/ELT pipelines using Python and SQL. Optimize cloud data workflows, support data models and integrations across Azure/AWS/GCP, monitor and troubleshoot pipelines, and collaborate with analysts and data scientists to deliver clean data for AI and analytics.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

Lead design and build of cloud-native, production-grade data platforms and real-time pipelines. Own architecture, implement scalable ingestion, storage, processing, and access layers, ensure security and governance, optimize performance, mentor engineers, and consult directly with clients to deliver data products and solutions.

Lead a data engineering team, develop AI self-service portal and data pipelines, interface with internal teams, and ensure software engineering best practices.

Design and build data architectures and pipelines, optimize data management, collaborate with AI teams, and implement best engineering practices.

Lead migration of a large-scale analytics platform from BigQuery to Databricks. Design and implement Lakehouse architectures, build and optimize PySpark data pipelines, implement medallion layers and Unity Catalog governance, troubleshoot complex SQL/Spark workloads, contribute to architecture and CI/CD, and support production deployments for retail analytics workloads.

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.

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.

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

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.

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.