Top Data Engineer Jobs in Germany

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 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.

Develop interactive data visualizations and enhance the chart library for Celonis, collaborating with cross-functional teams and advocating for UX best practices.

Develop scalable data pipelines and tools for forecasting and data analysis, ensuring high quality and integration within Statista's data architecture.

As a Software Developer & Data Engineer, you'll develop software solutions, maintain web applications, administer Azure services, ensure software quality, and manage databases, contributing to maritime process optimization.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

The Principal Data Engineer will improve data pipeline architecture, optimize data flows, and support data projects for various teams in the company.

The Senior Data Engineer will design and build high-performance data pipelines, ensuring data quality for AI applications, and promote best practices in data products optimized for machine learning.

As a Data Engineer at Zendesk, you'll build and maintain data pipelines and models, enhance data processing efficiency, and collaborate with teams to support CRM insights.

The (Senior) Data Engineer designs and maintains data pipelines, collaborates with clients on data needs, and develops dashboards for insights.

Design and build ETL pipelines and self-service data tools using modern cloud technologies, while collaborating with stakeholders to deliver data solutions.

Develop and maintain scalable data infrastructure and ETL pipelines, support machine learning applications, ensure data quality, and collaborate on data models.

As a Data Engineer at Helsing, you will lead and automate data acquisition and labeling processes for AI development, support data preparation pipelines, and collaborate with engineering teams.

As a Data Engineer at Screenverse, you'll build ETL pipelines, ensure data quality, and contribute to data strategy in a collaborative environment.

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.

As a Middle Data Engineer, migrate SQL Server data warehouses to Snowflake, refactor ETL processes, build data pipelines, and ensure reliable data movement.

As a Data Engineer, you will design data pipelines, implement storage solutions, refine data warehouse systems, and analyze infrastructure performance.

As a Data Engineer, you'll design, develop, and implement high-performance data infrastructure and pipelines while communicating effectively with various stakeholders.

As a Data Engineer, you will design and implement data pipelines, improve ETL processes, and ensure high performance of data infrastructure, while collaborating with clients to meet their goals.

As a Data Engineer, you will manage data ingestion workflows from Postgres to BigQuery, maintain data infrastructure, and contribute to data engineering pipelines while applying best practices.

The Big Data Engineer will architect and build data infrastructure, develop cloud-based processing pipelines, and ensure code quality for ML projects.

The Data Engineer will design and maintain ETL pipelines, optimize data models, develop exporters, and ensure reliable data services for the Lambda app in a fast-paced startup environment.

The Python Data Engineer will design and implement data pipelines, build integrations, develop APIs, ensure CI/CD compliance, and mentor team members.

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.

Join the Foundation Model Training team to develop and manage large-scale data pipelines for AI-driven language products, ensuring data quality and processing. Collaborate with research scientists to improve model training outcomes.