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# Data Engineer

- **Company:** Motor Gmbh
- **Location:** Berlin, Germany (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Artificial Neural Networks, Big Data, Information Systems, Databases, Data Cleansing, Information Engineering, Data Infrastructure, Data Integration, Data Warehousing, Python (Programming Language), Tensorflow, Standard Sql, Pytorch, Data Lakes, Information Technology, Data Pipelines
- **Published:** August 28, 2026
- **Apply:** https://www.adzuna.de/details/5859741676

## About the Role

* A completed degree in computer science, data engineering, data science, or a comparable field - or equivalent vocational training/apprenticeship in a relevant technical discipline. Hands-on experience counts at least as much as the formal qualification
 * 6+ years of experience as a Data Engineer
 * Experience designing and implementing data warehouses, data lakes, and information systems, and keeping live/production systems running - including participating in on-call and standby duty
 * Strong Python and SQL skills, with solid general database knowledge
 * Hands-on experience with TensorFlow and/or PyTorch, including at larger scale/setups, and experience training neural networks
 * Experience working with large data volumes and hybrid (cloud/on-prem) infrastructure setups, ideally in a small team with a broad scope of responsibility
 * Experience with data annotation and collaborating with external service providers
 * A strong ownership mindset and a pragmatic, hands-on approach to problem-solving, combined with good communication skills for close collaboration with AI Engineers, Perception, and Data Infrastructure
 * Fluent English is required; German is a plus

## Description

* Data Pipeline Development - Design, build, and maintain data pipelines that prepare, transform, and deliver data for AI and machine learning use cases
 * ML Data Integration - Ensure training and inference data is correctly structured, versioned, and accessible for AI Engineers and Data Scientists
 * Data Quality & Monitoring - Implement monitoring and validation checks to ensure the quality, consistency, and freshness of data feeding our AI systems
 * Tooling & Automation - Build and improve internal tooling to automate recurring data preparation and pipeline tasks, increasing team efficiency
 * Cross-Team Collaboration - Work closely with AI Engineers, Perception, and Data Infrastructure to align on data formats, access patterns, and pipeline requirements


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