Top Data Engineer Jobs in Hamburg

The Data Engineer will manage tracking data pipelines, ensure data quality and governance, optimize ELT processes, and collaborate with teams to enhance data accessibility and reliability.

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

Build and maintain scalable ETL/data pipelines and orchestration for content publishing, optimize and monitor data infrastructure, automate processes, and collaborate with data and content teams.

Responsible for deploying and maintaining data center infrastructure, troubleshooting hardware and network issues, managing inventory, and setting up data centers.

The role involves scaling the Feature Store, ensuring data quality, optimizing pipelines, and bridging data science with backend engineering in a mobile ad tech environment.

Lead design and implementation of scalable data architectures, pipelines and Data/AI features. Build reliable data warehouses and ETL, enable analytics, and collaborate with product, analysts and supply chain specialists to deliver optimized, production-ready solutions.

As a Senior Software Data Engineer, you will enhance and create data processing pipelines, monitor performance metrics, and enforce security practices within the Roads team at Mapbox.

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

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 Specialist Solution Architect will provide technical expertise to enterprise customers, leading technical sales and presentations while owning the sales process.

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.

The Technical Privacy Expert will implement privacy-by-design principles, ensure compliance with regulations, mentor teams, and develop technical frameworks for privacy in technologies.

The Data Engineer will enhance data retrieval pipelines, expand market coverage, develop features, improve monitoring tools, support API performance, and work with cross-functional teams in a dynamic environment.

As a Full-Stack ML Engineer, you will develop backend services, data pipelines, and customer-facing UIs while leveraging ML. You'll manage the software lifecycle and write code in Python and Typescript.

Design, build, and maintain backend services and automation for data pipelines and internal tooling. Integrate AI/ML features, own CI/CD and observability, lead code reviews, and collaborate with cross-functional teams to ensure scalable, reliable production systems.

As a Senior Software Engineer at ClickHouse, you'll enhance the Python data ecosystem by creating tools and integrations for data practitioners, focusing on performance and reliability while collaborating with various teams.

The Software Engineer will manage data collection and processing to enhance AI model training, collaborating with scientists and extending cloud infrastructure.

As a Big Data Engineer, you will design and implement data processing systems, manage technologies like Hadoop and Spark, and build ETL processes to ensure data quality and performance.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

The Staff Engineer will define architecture, lead data pipeline design, ensure platform reliability, and mentor engineers, driving data initiatives and technical standards.

The Data Engineer will design and maintain data pipelines, optimize ETL processes, ensure data quality, and collaborate in an agile environment.

The Staff Data Engineer will develop statistical models, analyze complex data for insights, and enhance performance optimization through machine learning algorithms and data orchestration tools.

Design and maintain data pipelines, collaborate with stakeholders, ensure data quality, deploy infrastructure as code, and optimize reporting solutions.

Design and develop data models, ETL processes, and cloud-based data solutions using Azure and various big data technologies. Support report generation and data analysis.

The role involves creating and automating infrastructure features for data platforms using Python, with a focus on distributed systems and collaboration within a global team.