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Embedded Python Integration Engineer

Embedded Python Integration Engineer
VON Consulting
4 months ago


  • Check completeness of CI/CD (continuous integration/deployment) build activities.
  • Collaborate with IT and maintain the lab infra – this will slowly be transferred from existing team to the new person.
  • Example: check if data from boards-database matches with actual data and Lauterbach/Reset device is unique to this device.
  • Slowly start developing Jenkins pipelines, enhance existing infra config and ultimately, become one-point contact for all release-related integration activities.
  • Over the course, train to understand embedded code so you can get familiar with project code to provide improvements related to CI/CD activities (releases, quality, release scripts etc).


  1. Overview: Python, Embedded, C,C++, some basic CI/CD knowledge.
  2. Mandatory skills:
    1. Medium level embedded C with debugging knowledge (gdb, Lauterbach or equivalent debuggers); pointers, memory understanding are a must.
    2. Python scripting knowledge – ability to develop small features in oops concepts, debug issues in .py scripts of the current framework, idea on python processes.
    3. Some basic understanding of DevOps workflow – SCM, CI build systems
      1. Jenkins can be trained from DevOps team.
      2. Knowledge on git basics, PR and CI/CD workflow – needed.
  3. Good to have skills:
    • Basic networking knowledge (ARP, DHCP, what is static/dynamic IP, MAC, firewall aso); no in-depth knowledge is needed, just the basic concepts.
    • Strong problem solving ability and independent work-oriented preferred (be confident in setting up new hardware, know ESD regulations etc).
    • Advanced knowledge of C/C++ concepts (data structures, memory allocation, best practices etc).
    • In-depth knowledge of Python or a high-level language (Java, C#, Go).
    • Very good analytical thinking to solve first seen issues, especially debugging.
    • Preferable knowledge or work experience of advanced Jenkins/any CI pipelines with experience in a virtualized container (KVM, Podman, Docker etc).

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