Degree in Computer Science/Engineering, or equivalent experience
2+ years of relevant professional experience building and deploying data solutions
Strong proficiency in Python and SQL for data engineering and experience writing robust, production-grade code, including deploying code across environments
Proven experience building end-to-end data pipelines and platforms for Agentic AI, Generative AI, Machine Learning, or Business Intelligence, covering data preparation, embeddings generation, vector search, and system integration using modern frameworks (Spark, dbt, LangChain)
A strong foundation in system design, data storage, and reliability with commonly used data platforms (Databricks, Snowflake, BigQuery, PSQL, etc.) and data engineering tools (e.g., Pandas, Spark, dbt, etc.)
Hands-on experience with MLOps/LLMOps principles, including CI/CD for data workflows, automated agent evaluation (LangSmith, Opik, Langfuse), and infrastructure as code (Terraform)
Experience building systems with different data formats (structured vs unstructured) and data processing methods (streaming vs batch) and deploying across major cloud platforms (AWS, Azure, GCP)
Exceptional time management in a complex and largely autonomous work environment
Commercial client-facing or senior stakeholder management experience is beneficial
Experience using coding agents (Cursor, Claude Code, Codex, etc.) is a plus
Strong communication skills, both verbal and written, in German and English