Top Data Engineer Jobs in Poland

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

As a Data Engineer, you will design metrics, build reports, analyze data trends, and collaborate with cross-functional teams to enhance data-driven decision-making.

As a Web Scraping Engineer, you will develop tools for processing big and unstructured data, ensuring accuracy and compliance through extensive testing and maintenance of scrapes.

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

The role involves developing software for road features, improving data processing pipelines, monitoring performance, and implementing security best practices.

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

The Data Engineer will design and develop data pipelines using Azure Databricks, implement ETL processes, maintain data architecture, and ensure data quality, collaborating with BI teams and support existing SQL Server platforms.

The Data Engineer will design and develop data pipelines and Lakehouse architectures using Azure Databricks, ensuring data quality and performance while integrating with existing environments.

The Data Engineer will design and develop data pipelines and Lakehouse architectures using Azure Databricks, optimize data transformations, and ensure data quality and performance for analytics.

The Data Engineer will design and develop data pipelines and Lakehouse architectures on Azure, ensuring data quality and integrating multiple data sources.

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.

Join our team to implement and maintain a Customer Data Platform (CDP) including data pipeline construction, user identification mechanisms, and collaboration across various teams.

Design and maintain data pipelines while optimizing data warehouses, collaborating with analysts and scientists, and ensuring data integrity through quality measures.

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 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.

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

The Data Engineer will optimize backend services for a SaaS platform, develop data pipelines using SQL and Python, and collaborate in an Agile environment to implement cloud solutions on Microsoft Azure.

Looking for a Data Engineer to implement cloud-native data platforms, engineer scalable pipelines, and manage cloud resources. Ideal candidates have strong Python and SQL skills, and experience with tools like Spark and Terraform. Familiarity with MLOps is a plus.

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.

Design and build data pipelines for ingestion and analytics, ensuring data quality and supporting machine learning needs in a collaborative environment.