Working Student - Data Engineering (f/m/x)

Who we are Founded in 2019, Marvel Fusion is Europe’s leading fusion energy company, uniting 75 scientists, engineers, and entrepreneurs across our locations in Munich and Colorado.  Backed by over €385 million in public and private funding, we’re driven by a shared mission: to deliver clean, abundant energy to the world.  Why Marvel Fusion By joining us, you will be: Solving one of the most complex technological challenges known to humanity, harnessing Fusion on Earth Part of a highly purpose-driven team working on providing the world with clean, safe and abundant energy Working alongside world-leading scientists and entrepreneurs in the field of Fusion Part of a start-up where growth on a company and individual level is the default Your responsibilities In this role, you will:  Support the development of internal tools that help scientists and engineers work with experimental data Gain hands-on exposure to experimental control systems and support data-related activities during experimental campaigns Improve the reliability of data pipelines through debugging, testing, monitoring, and clear documentation Contribute to scalable and well-structured data processes that support reproducible scientific work Create dashboards, panels, and indicators that make technical systems easier to monitor and understand What you bring Must-have: Enrolled in Physics, Computer Science, Software Engineering, Data Science, or a related field (3rd year Bachelor's or Master's level) Enjoyment of programming and solid basics – or the motivation to build them – in Python, C++, Bash, and Linux Basic understanding of databases and how structured data is stored, queried, and organized Familiarity with core operating-system and systems-administration concepts Clear communication in English and the ability to explain technical problems in a structured way A proactive, reliable, and curious mindset – you take ownership and ask good questions At least 6 months of remaining student status and availability for 20 hours per week Nice to have: Familiarity with Data Acquisition (DAQ) systems, experimental control, or scientific measurement workflows Hands-on experience with electronics, instrumentation, embedded systems, or low-level software Experience with Git and collaborative development practices Exposure to automation, CI/CD, or infrastructure concepts Working knowledge of SQL or interest in data modeling and data-management best practices For more information on how we process your application data, please review our privacy notice.