Top Data Engineer Jobs in Warsaw

The Data Engineer will design and implement data migration solutions, develop pipelines and ensure data quality for audiology solutions.

Design and optimize databases and data processing systems, collaborate with developers, gather user requirements, and provide user support.

As a Data Engineer, you'll design robust data pipelines, optimize data architectures, ensure data quality, and support analytics efforts while collaborating with stakeholders.

As a Senior Robotics Data Engineer, you will manage vision system data streams, ensure data quality for AI training, and collaborate on innovative robotics solutions.

Design, develop, and optimize Informatica PowerCenter mappings, workflows, and PowerExchange integrations across Oracle, DB2, Snowflake, Linux, and mainframe systems. Perform SQL/PLSQL development, database and ETL performance tuning, shell scripting for automation, and support production operations and incident management while translating business requirements into scalable data integration solutions.

The Senior Data Engineer will design, build, and maintain data systems, pipelines, and infrastructure for data processing and analysis, collaborating with stakeholders and ensuring data quality.

As a Principal Big Data Engineer, you will design scalable solutions, develop data pipelines, create features, and collaborate with various teams to enhance Akamai's data platform.

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.

As a Data Engineer, you will lead data initiatives, build scalable ETL pipelines, ensure data quality, and collaborate with teams to drive data-driven decisions.

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.

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

The Data Engineer will design and maintain scalable data pipelines, optimize data infrastructure, monitor data quality, and enable analytics capabilities, ensuring alignment with business goals.

Design, build, and deploy large-scale distributed systems and high-throughput data pipelines. Lead architecture and technical initiatives, ensure performance, resilience, and SLAs, contribute production-quality code, and mentor engineers while collaborating with product and R&D leadership.

Design, build, and operate large-scale distributed systems and high-throughput data pipelines using Go and cloud-native technologies. Lead architecture, performance optimization, reliability SLAs, and code quality. Drive technical roadmap, mentor engineers, reduce technical debt, and collaborate with product and engineering teams.

Design, build, and deploy large-scale distributed systems and high-throughput data pipelines using Go and cloud-native technologies. Lead architecture decisions, ensure performance and resilience, contribute high-quality code, reduce technical debt, and mentor engineers while collaborating with product and engineering teams.

Design, build, and own large-scale distributed systems and high-throughput data pipelines. Lead architecture, improve performance and resilience, reduce technical debt, contribute code, and mentor engineers while collaborating with product and R&D.

Design, build, and operate enterprise reporting and analytics platforms. Create scalable ELT/ETL pipelines, master data foundations, and lakehouse/warehouse semantic models. Deliver Power BI datasets and dashboards, implement data quality, governance, DevOps practices, and cost-management data solutions. Partner with finance and stakeholders and provide technical leadership across architecture, deployment, and run-state support.

Design and build the knowledge layer for AI agents that represent brand identity and reasoning. Develop agentic search, dynamic retrieval, and RAG systems; evaluate retrieval/reasoning architectures; translate AI research into production systems; collaborate with product and AI teams to improve user-facing outcomes.

Design and deliver data solutions including data marts and dashboards, optimizing performance, implementing governance frameworks, and mentoring team members.

Build, maintain, and scale ELT data pipelines and dbt models on Google BigQuery. Write Python for data processing, ensure data quality, monitor pipelines, collaborate with analytics/product/game teams, and contribute to data architecture in a fast-paced startup.

Design, build, and maintain ELT pipelines; develop, test, and document dbt models; optimize and query Google BigQuery; write Python for data processing; ensure data quality and reliability; monitor and troubleshoot pipelines; collaborate with analytics, product, and game teams and influence data architecture.