Semantic Product Information Architect

The Corporate PLM Office and the Center of Competence (CoC) PLM shape the future product data landscape at B. Braun. A key building block is the creation of a Semantic Web for product information that makes information clearly interpretable, linkable and machine-readable across systems, processes and organizational boundaries. To strengthen the team, an experienced Semantic Product Information Architect is sought. In this strategic and technical role, you design, model and implement an Enterprise Product Knowledge Graph as the semantic information layer for the digital product lifecycle.

• Design, build and further development of an Enterprise Product Knowledge Graph, and modeling and implementation of semantic information models and ontologies based on RDF, RDFS and OWL.
• Definition of information objects, classes, properties, semantic relationships, taxonomies, vocabularies, namespaces and reusable semantic patterns along the product lifecycle.
• Development of SHACL shapes and rules to validate semantic data, and use of SPARQL to analyze, validate and query the knowledge graph.
• Implementation and maintenance of semantic models in a suitable knowledge graph/Semantic Web platform, and definition and maintenance of mappings between semantic information objects and operational data structures.
• Semantic linking of product information with the underlying data records and systems of record, and ensuring consistency and traceability between semantics, knowledge graph and operational data sources.
• Establishing governance, versioning and modeling guidelines for ontologies and semantic information models.
• Close collaboration with PLM, Corporate Data Framework (CDF), Data Intelligence Platform (DIP), data governance and enterprise architecture, as well as advising departments and moderating related workshops.

• Completed degree in computer science, business informatics, engineering or a comparable field, plus several years of experience in Semantic Web, knowledge graphs, ontology engineering, information architecture, data governance or PLM.
• Hands-on experience with RDF, RDFS, OWL and SHACL, plus good knowledge of SPARQL and graph-based query models.
• Experience with knowledge graph or Semantic Web platforms, for example Linksphere, GraphDB, Stardog, TopBraid EDG, Protégé or comparable technologies.
• Experience in modeling ontologies, classes, properties, relationships, taxonomies and metadata, plus understanding of URI/IRI, namespaces and linked data principles.
• Experience mapping operational data structures to semantic information models; knowledge of product data structures and Product Lifecycle Management is an advantage.
• Knowledge of MBSE, systems engineering or enterprise architecture and experience in regulated industries such as medical technology, pharma or life sciences are an advantage.
• Strong conceptual and analytical thinking, a structured and solution-oriented way of working, strong communication and facilitation skills, and enthusiasm for Semantic Web, knowledge graphs, data quality and AI-ready information.