Senior Data Engineer (m/f/d)

eigenblue – We're building the future of engineering. A future where engineers build intelligent systems that solve complex problems, and work alongside those systems to bring their solutions into the real world. We solve complex, multidisciplinary engineering problems by combining deep human expertise with AI systems we build ourselves. Our proprietary AI models generate system architectures across software, electronics, mechanics, and applied physics - and our engineers stay in the loop, not as supervisors but as the decisive factor to bring those architectures into the real world.

As Senior Data Engineer (m/f/d) you will be at the forefront of building our data infrastructure for our AI product from the ground up. You'll architect and implement scalable data platforms and advanced RAG pipelines that power our proprietary AI systems, working alongside AI engineers and cross-functional teams to bring cutting-edge reasoning models to life.

Your Role

• Build data and analytics platforms at scale, including data stores/warehouses and RAG pipelines for AI systems and reasoning models that go beyond standard LLMs • Work with AI Engineers to design, implement, and test innovative ideas for advanced AI reasoning, using our proprietary ontology and algorithms combined with public tools and data • Visualize data with dashboarding & analytics solutions and mentor other engineers on data engineering best practices, ensuring we build high-quality solutions for our customers • Improve our approach for quality assurance and data ingestion by introducing new tools and frameworks • Collaborate closely with various stakeholders, such as AI Engineers, Product Managers, Chief Officers and Software Teams, to integrate AI features into user-facing products

Your Profile

• University degree in Computer Science, Software Engineering, Data Science/Engineering or related disciplines, and 4+ years of experience in agile development projects • Experience with data engineering for ML/AI production deployment/MLOps using cloud platforms (Azure, AWS and/or GCP) and designing architectures for data platforms and data processing pipelines, building batch and real-time streaming solutions leveraging e.g. PySpark or Kafka • Experience with data warehousing services (AWS Redshift, Snowflake), LLM data stores, SQL/no-SQL tools and data management processes • Strong analytical and problem solving skills, comfortable with ambiguity and rapid changes common in early-stage product development • Additional expertise with AI tools and LLM providers, implementing advanced RAG pipelines (e.g., GraphRAG), agents/MCP, multi-agent architectures, ML model training, LLM fine-tuning, RLHF, LLM-as-a-judge metrics, and working in a multidisciplinary environment on customer-facing products and research projects • Excellent verbal and written communication skills in the English language, with the ability to collaborate effectively across multidisciplinary teams