Top Data Engineer Jobs in Poland

As a Data Engineer, build and manage data pipelines, ensure data quality, and support analytics for trading. Collaborate with teams to define data needs and best practices for infrastructure and applications.

The Data Engineer develops ETL/ELT pipelines and data warehousing solutions, collaborating with teams to enhance data capabilities at UL Solutions.

As a Data Engineer at Zapier, you'll build scalable data systems, enhance product functionality through data, and collaborate with teams to improve data access and usability.

As a Full Stack Engineer, you will develop features for the analytics platform using Java and TypeScript, focusing on backend services and React apps, enhancing the software observability product.

The Data Engineer will develop and optimize data pipelines, improve architectural solutions, and collaborate across teams to deliver data-driven insights.

Design and architect scalable backend services, develop robust governance systems, build SaaS solutions, and mentor junior engineers to enhance IoT platform capabilities.

The Data Platform Engineer will develop and maintain data lakes and pipelines, propose improvements, and ensure best practices in data engineering.

As a Senior Backend Data Engineer, you'll design large-scale data pipelines, develop backend services, and collaborate with cross-functional teams to enhance digital environments.

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

The Data Engineer will design and implement data pipelines, databases, and processing systems, ensuring data security and integrity while collaborating with stakeholders.

The Data Engineer will build a creative intelligence pipeline, connecting ad data to ETL processes, enabling time-series queries, and documenting the setup for handoff.

Design and automate data pipelines, develop systems for storing operational data, ensure data quality, and collaborate with data scientists.

Join dentsu as a Data Engineer, focusing on ETL processes, cloud administration, and data warehouse maintenance within Google Cloud. Responsibilities include building scalable ETL workflows, writing code, managing data pipelines, and collaborating on ML solutions.

The Data Engineer builds and supports data pipelines, develops data warehouses, and creates monitoring dashboards to improve data processing reliability.

The Data Engineer is responsible for data collection, sanitization, transformation, and integration into reports to support business decisions. The role involves designing data pipelines, troubleshooting issues, and ensuring data quality in collaboration with a global team.

The Data Engineer will design and implement scalable data solutions on AWS, manage data pipelines, enforce data governance, and collaborate with teams to enhance processes while troubleshooting challenges.

Develop and maintain a Customer Data Platform (CDP), integrating event data, building data pipelines, and collaborating with various teams on user identification mechanisms.

The role involves developing innovative Data & Analytics products, enhancing existing solutions, and creating Tableau dashboards while ensuring data integrity and compliance in collaboration with finance stakeholders.

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 Senior QA Engineer will execute manual and automated tests, collaborate on requirements, support UAT, and ensure software quality for financial systems.

The Data Engineer will build and optimize data pipelines and architectures for analytics, ensuring data quality and reliability while collaborating with various teams.

As a Data Engineer, you'll maintain and configure the Snowflake data platform, design integration pipelines, and innovate with new tools. Your role supports data security and performance while collaborating across teams.

As a Data Engineer, you'll design and optimize data pipelines on Databricks, implement scalable data models, and collaborate with AI teams for advanced analytics and security integrations.

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

Design and implement customer data integrations, optimize SQL for analytics, and collaborate with teams to ensure data integration success.