(Senior) Data Engineer (f/m/d): SAP Data on RDF Knowledge Graphs

You will build the data foundation for SAP’s Knowledge Graphs and enable scalable, high-quality data for AI-enabled business applications. You’ll design robust data pipelines, map data to ontologies, and operate RDF stores in production alongside cross-functional teams. This role blends data engineering, knowledge graphs, and generative AI to reduce hallucinations and enable advanced AI solutions. You’ll work in a global AI organization that values learning, collaboration, and impact.

• great benefits
• constant learning and skill growth
• team focused on personal development
• global collaboration
• flexible working models

• Build the data foundation for SAP’s Knowledge Graphs across multiple domains
• Design and operate scalable data pipelines ingesting structured and unstructured data into RDF Knowledge Graphs
• Map source data to ontologies and SHACL schemas; develop SPARQL-based transformations
• Collaborate with domain experts to translate requirements into KG data flows
• Make design decisions on data engineering stack (triple stores, ETL/ELT, orchestration, integration with Generative AI)
• Contribute thought leadership at the intersection of Data Engineering, Knowledge Graphs, and Generative AI
• Present and advocate for high-quality KG data to stakeholders and propose new use cases

• PhD or Master’s degree in relevant disciplines
• 2+ years in Data Engineering with knowledge graphs in a business context
• Experience designing large-scale batch and streaming data pipelines
• Deep proficiency in RDF stack (RDF, RDFS, OWL, SHACL, SPARQL) and triple stores; familiarity with property graph solutions a plus
• Experience mapping operations into data models, ontologies, schemas
• Working knowledge of triple stores and KG architectures (GraphDB, Stardog, Virtuoso, Apache Jena, Blazegraph)
• Awareness of KG construction from unstructured data, graph RAG, KG embeddings
• SQL, data warehousing/lakehouse concepts, and cloud platforms (AWS, GCP, Azure, Databricks)
• Fluent in Python; ability to translate ideas into code
• Ability to advise stakeholders on enterprise KG adoption and business use cases
• Knowledge of SAP data and applications preferred
• Strong communication and cross-cultural collaboration skills

• strong communication
• collaboration
• stakeholder advisory
• RDF, RDFS, OWL, SHACL, SPARQL
• triple stores (GraphDB, Stardog, Virtuoso, Apache Jena, Blazegraph)
• Neo4j (property graph) - plus