Data Engineer / AI Specialist (w/m/d) Factory Digitalization | Data Engineer / AI Specialist (w/m/d) Factory Digitalization

Siemens AG

Leipzig, Sachsen, Deutschland
Published Feb 13, 2026
Full-time
No information

Job Summary

This role offers the opportunity to act as an architect for data infrastructure within Siemens' manufacturing sites, driving digital transformation through innovative AI solutions. Day-to-day, you will evaluate data source accuracy, design and implement ETL data pipelines for cloud-based systems, and ensure the integrity and consistency of data structures. You will collaborate with cross-functional manufacturing departments to identify AI use cases, conduct pilot projects, and translate complex data insights into actionable improvements for products and processes. The position is ideal for those who enjoy bridging the gap between technical modeling and business application. It is particularly attractive due to its focus on cutting-edge technologies like Large Language Model frameworks and cloud platforms, combined with a flexible work model requiring only 2-3 days of on-site presence and a comprehensive benefits package including employee stock plans.

Required Skills

Education

Master's degree in Computer Science, Informatics, Business Mathematics, or a related field with a focus on Data Engineering.

Experience

  • Several years of professional experience in the integration of multiple tools and data sources such as search indices, databases, and ERP systems.
  • Experience with AI frameworks such as LangChain, LlamaIndex, or Semantic Kernel.
  • Proven proficiency in SQL and Python for data manipulation and requests.
  • Experience in Prompt Engineering and understanding of MCP interfaces and tool calls.
  • Initial experience or knowledge in handling cloud computing platforms like AWS or Azure.
  • Experience in analyzing business processes to identify suitable AI use cases.

Languages

German (Fluent)English (Fluent)

Additional

  • The position requires a physical presence of 2-3 days per week at the site. Candidates must possess the ability to present complex technical findings to non-technical audiences.