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.

As a Backend Data Engineer, you will design and maintain data pipelines, implement features for marketing analytics, and collaborate with various teams while ensuring system performance and data quality.

The Data Engineer will design and maintain data pipelines and architectures, ensuring reliable data for decision-making through collaboration with data analysts and scientists.

The Machine Learning Engineer will design, build, and deploy scalable ML solutions, collaborating with teams to operationalize models and ensure their performance and reliability.

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.

Design, develop, and maintain user-facing features using Java, ensuring high standards of code quality, troubleshooting issues, and collaborating with a team.

Design and develop AI applications, deploy machine learning models, integrate AI into business systems, and work with cross-functional teams to create AI-driven solutions.

Join an analytics team to build and maintain data models, automate data pipelines, and contribute to an AI agent, translating business needs into technical solutions.

As a Principal Database Engineer, you will architect scalable PostgreSQL solutions, ensuring data reliability, performance, and collaborating with teams to build a robust data platform for GitLab's growth.

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.

Design, develop, and maintain data pipelines and Lakehouse architectures using Azure Databricks, Spark, and SQL Server, focusing on performance and scalability.

The role involves designing and developing data pipelines and Lakehouse architectures using Azure Databricks, optimizing data transformations, and integrating various data sources for analytics.

Design and develop data pipelines and Lakehouse architectures using Azure Databricks, while integrating with existing SQL Server data environments and enabling advanced analytics.

Design and implement scalable batch and streaming data pipelines on Databricks and cloud platforms; build data transformations, CI/CD and MLOps practices; collaborate with data scientists; create data governance, monitoring, and Power BI visualizations; translate business requirements into performant technical solutions.

Build and maintain scalable batch and streaming data pipelines using Databricks, Spark, Airflow/Dagster and DBT; implement CI/CD and DevOps practices; support ML projects and Power BI reporting; translate business requirements into performant data solutions.

Design, build, and maintain scalable data pipelines and platforms for batch and streaming data using Spark, Airflow, Iceberg, and cloud services. Optimize ingestion, processing, and storage, collaborate with stakeholders, monitor platform performance, and write high-quality Python/Java/Scala code to support enterprise reporting and analytics.

Design and develop cloud-based data pipelines, automate testing, and ensure security and performance while collaborating with teams to deliver efficient solutions.

Develop scalable software, collaborate on design and architecture, conduct code reviews, and mentor new team members in a high-performance environment.

The Analytics Engineer will design and implement data integration solutions (ETL) for data analytics, build data models, and improve data infrastructure.

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.

The Azure Data Engineer will design, architect, and implement secure cloud-native data platforms on Azure, focusing on data accessibility for applications and GenAI services.

The Senior Software Engineer will lead engineering teams, mentor junior engineers, and ensure system reliability and performance while developing backend services.

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

Design and operate scalable Java-based backend services, develop APIs, build data pipelines, and collaborate with cross-functional teams for personalized solutions.