Data Governance and Analytics Specialist | Data-governance (m/w/d) ANÜ

HOLZER Firmengruppe

München, Bayern, Deutschland
Published Mar 19, 2026
Full-time
No information

Job Summary

This role focuses on establishing and managing structured data collection and evaluation processes using Mobile Data Recorders (MDR) within an Azure Cloud architecture. The successful candidate will be responsible for the operation and maintenance of MDR systems in test vehicle fleets, ensuring error-free data collection through automated check-ins and diagnostic traces. Day-to-day tasks involve processing, analyzing, and visualizing large datasets using Microsoft Azure and KQL to identify patterns in vehicle electrical/electronic (E/E) systems. A unique aspect of this position is the opportunity to develop and implement AI applications to improve system stability and robustness. Working within a traditional motorsport environment, you will collaborate closely with project managers and functional leads to translate complex data into actionable management reports. This position is ideal for professionals who enjoy combining hands-on hardware integration with high-level cloud analytics and artificial intelligence in the automotive sector.

Required Skills

Education

University degree in Computer Science, Electrical Engineering, Engineering with an IT focus, or a comparable qualification.

Experience

  • Professional experience in data analytics, artificial intelligence (AI), and data engineering
  • Experience in the automotive E/E (Electrical/Electronic) environment is preferred
  • Experience in managing and optimizing MDR integration in vehicles
  • Proven track record in processing and visualizing large volumes of data within cloud architectures
  • Experience in developing AI applications for system stability and security

Languages

German (Fluent)English (Fluent)

Additional

  • This position is offered via temporary employment (ANÜ). Candidates must be able to work in a mid-sized motorsport company environment and collaborate across interdisciplinary teams.