Top Data Engineer Jobs in Poland

As a Junior Associate Engineer in Data, you'll design, build, and maintain data systems and pipelines to process and analyze large volumes of data, ensuring data quality and integration from diverse sources, while collaborating with analysts and stakeholders.

Design and lead the development of data infrastructure and pipelines, ensuring operational excellence and data quality while mentoring teams.

Seeking a Senior Software Engineer to design scalable solutions, optimize performance, and collaborate with cross-functional teams to enhance data management and analytics.

The Senior Data Engineer will design and maintain data systems, build data pipelines, optimize ETL processes, and ensure data quality, collaborating with various teams to facilitate data-driven decision making.

The Data Engineering Lead is responsible for designing and optimizing data architectures, overseeing data systems, mentoring team members, and ensuring high-performance data processes that align with business goals.

Lead the design and optimization of scalable data solutions, overseeing data quality, mentoring team members, and collaborating with cross-functional partners to drive data products and ensure compliance with data regulations.

The Junior Data Engineer will analyze data, design experiments, build a marketing data stack, and collaborate with teams to improve data access and insights.

As a Senior/Expert ML/Data Engineer, you will build data pipelines and ML models, focusing on AI/ML innovations, mentoring, and optimizing data solutions.

The Junior Data Engineer coordinates data integration projects, collaborates on data solutions, and ensures data integrity while working with various teams and stakeholders.

The Lead AWS Software Data Engineer will design and develop scalable data pipelines using Python and AWS tools, collaborate with business teams, and enhance data quality and observability while applying modern software engineering practices.

Develop AI-powered data mapping recommendation platform, automate data extraction and validation, build scalable data pipelines, and manage data governance.

As a Data Engineer II, you will design scalable data pipelines in AWS, develop SQL transformations, and enhance MLOps workflows, focusing on analytics and machine learning initiatives.

Design, build, and maintain scalable GCP data pipelines and ETL/reverse ETL processes using Dataflow, Dataform, and BigQuery. Develop secure APIs for ingestion, optimize data models and Datastream integrations, implement monitoring, and ensure GDPR/CCPA-compliant data governance for player analytics and fraud detection.

The Data Engineer will build and maintain ETL pipelines, develop data workflows, ensure data quality, and integrate systems within a cloud environment.

Develop reusable data pipelines, optimize ETL processes, build data integrations, and improve data platform architecture while collaborating with cross-functional teams.

The role involves developing and maintaining data pipelines and backend APIs using Python, while collaborating with teams to integrate AWS services.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

The GIS Software Engineer will architect and implement scalable GIS solutions, collaborate with teams, and monitor production services while ensuring security and performance.

The Middle Data Engineer will design and maintain data pipelines, manage cloud-based solutions, and resolve data issues while collaborating with teams.

The Data Engineer will build and maintain the data platform, optimize data transformations, implement data governance, and collaborate on data assets to ensure data-driven decision making.

The Data Engineer will design and maintain data pipelines, optimize performance, enforce governance, and collaborate with AI teams for innovative solutions.

Build and maintain Python-based data pipelines on Databricks, collaborate with product and domain experts, debug Tier-2 system issues, create documentation and onboarding processes, write integration tests, manage code in GitLab, and improve data quality and self-service tooling.

Design, build, deploy, and maintain scalable data products and pipelines. Collaborate with BI and analytics teams to manage the data stack, implement data quality, observability, and governance, and enable automation and self-service for stakeholders across the organization.

Design, build, and maintain ETL pipelines, data warehouses, and data models; integrate and monitor data sources; ensure data quality and lineage; collaborate with Data & Analytics stakeholders and provide documentation and training.

Design, build and maintain large-scale ETL pipelines and data models using big-data tools. Develop reusable code, schedule and monitor Airflow DAGs, ensure data quality, debug production issues, and collaborate with stakeholders to deliver analytics and AI-ready data assets.