Research Data Steward / Data Architect | Research Data Steward / Data Architect (m/f/d, E13 TV-L, 100%)
Eberhard Karls Universität Tübingen Personalverwaltung
Job Summary
This role is based within the Machine Learning Science Cloud at the University of Tübingen, where you will play a pivotal part in building modern HPC architecture for large-scale scientific research and foundation models. Day-to-day, you will develop storage strategies, design data pipelines for research datasets on HPC infrastructure, and implement FAIR data strategies. You will act as a bridge between technical infrastructure and research needs, advising scientists on data management plans and ensuring high-performance data accessibility for AI experiments. The position is highly attractive due to its long-term stability (running until 2032) and the opportunity to work in a vibrant, international environment with over 200 researchers. You will have access to cutting-edge hardware and contribute to diverse projects ranging from climate science to large language models, making it an ideal role for those passionate about the intersection of data engineering and advanced scientific research.
Required Skills
Education
Master’s degree in Information Technology, Applied Computer Science, Computer Engineering, or a comparable degree.
Experience
- Professional experience in data engineering and data pipeline implementation
- Demonstrated experience working with HPC clusters and parallel file systems
- Experience with Linux system administration and shell scripting
- Practical knowledge of research data management and FAIR principles
- Experience with containerization technologies and automation tools for configuration management
- Experience in hardware technologies including CPU, GPU, and RAID storage systems
Languages
Additional
- The position is a full-time (100%) role based in Tübingen, Germany, classified under E13 TV-L. It is a fixed-term contract running until December 31, 2032. Candidates must be able to coordinate with legal/compliance teams regarding data protection requirements.
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