Top Data Engineer Jobs in Warsaw

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.

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

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.

The Data Engineer will develop automated data management solutions, design ETL processes, ensure data quality, and create dashboards for actionable insights, facilitating data-driven decisions for clients.

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

The Marketing Data Engineer will architect and build data systems, develop integrations, advance analytics, automate workflows, and ensure data quality.

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.

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 Senior Data Engineer will design and develop ETL pipelines, ensure data quality and integration, and mentor junior engineers.

Design, build, and maintain data pipelines and ETL processes; model and optimize data storage; ensure data quality and governance; collaborate with data scientists and analysts to deliver analytics-ready datasets and document data systems.

As a Data Engineer, you will develop and support big data processing pipelines, build cloud-based infrastructure, and provide visualization solutions for data assets.

As a Data Engineer, you will design and maintain data pipelines, automate workflows, and resolve issues in complex systems. You will collaborate with teams to enhance operational efficiency and ensure data accuracy.

As a Data Engineer, you will develop and optimize data pipelines, implement advanced analytics, and collaborate with stakeholders to enhance data systems.

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

Design and maintain scalable data pipelines, optimize performance, and collaborate with teams to improve data quality and governance.

As a Data Engineer II, you'll design and maintain data infrastructure, build data pipelines, and ensure data quality and performance while collaborating with cross-functional teams.

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.

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

As a Data Engineer, you will enhance our data platform, build scalable architecture, optimize data transformations, and ensure data governance across teams.

The Data Engineer will design and implement scalable data platforms, build data pipelines, collaborate with teams to ensure data quality, and streamline processes using AWS services and big data technologies.