2 months ago
Garching bei München, GermanySenior
Responsibilities
- Design and build scalable batch and streaming data pipelines for structured and unstructured SAP and non-SAP business data.
- Map source data into ontologies and SHACL schemas and develop SPARQL-based transformations.
- Operate RDF triple stores in production and contribute to Knowledge Graph data provisioning.
- Understand SAP data models, business objects, source systems, and table-level data structures.
- Make design decisions about triple stores, ETL/ELT tooling, orchestration, and downstream Generative AI integration.
- Collaborate with domain specialists, data owners, Knowledge Engineering teams, Data Engineering teams, and other stakeholders.
- Advise stakeholders on bringing data into enterprise Knowledge Graphs and identifying business use cases.
- Contribute thought leadership at the intersection of Data Engineering, Knowledge Graphs, and Generative AI.
Requirements
- PhD or Master’s degree in computer science, artificial intelligence, physics, mathematics, or another relevant discipline.
- At least 2 years of related professional experience in Data Engineering, ideally including business Knowledge Graphs.
- Experience designing and operating large-scale batch and streaming data pipelines with modern Data Engineering tooling.
- Strong knowledge of SAP data and SAP applications, including their data models, business objects, and table-level structures.
- Experience mapping business operations and source systems into data models, ontologies, and organized schemas.
- Awareness of Knowledge Graph and LLM trends including Knowledge Graph construction from unstructured data, graph RAG, and Knowledge Graph embeddings.
- Strong SQL skills and knowledge of data warehousing, lakehouse concepts, and cloud data platforms such as AWS, GCP, Azure, and Databricks.
- Fluency in Python and the ability to develop productive code hands-on.
- Working proficiency with RDF, RDFS, OWL, SHACL, SPARQL, and triple-store operations.
- Familiarity with property graph solutions such as Neo4j is preferred.
- Knowledge of triple-store technologies such as GraphDB, Stardog, Virtuoso, Apache Jena, and Blazegraph is preferred.
- Ability to advise diverse stakeholders and strong communication and collaboration skills in cross-cultural teams.
Benefits
- Regular full-time employment with 0–10% expected travel.
- Flexible working models and an international, collaborative AI team environment.
- Opportunities for continuous learning, personal development, and skill growth.
- SAP health and well-being support, inclusion initiatives, and accessibility accommodations.
- Hybrid work arrangement indicated by the #LI-Hybrid designation.
Tech Stack
Categories
Data Engineering
About SAP
SAP builds enterprise application software and cloud services for finance, procurement, supply chain, human resources, and analytics, sold through subscriptions, licenses, and support. Its portfolio includes SAP S/4HANA, SAP Business Technology Platform, SAP Ariba, and SAP SuccessFactors. Founded in 1972 and headquartered in Walldorf, Germany, SAP is a public company listed on the NYSE and Frankfurt (ETR) and serves enterprises and public-sector organizations worldwide.