Reference Data Governance Specialist
Core
Design, build, maintain, and govern enterprise reference data models, controlled vocabularies, taxonomies, ontologies, and semantic data assets to support enterprise semantic data and knowledge graph initiatives.
Role type
Reference Data Governance Specialist (Semantic Data & Knowledge Graphs)
Builds
Enterprise reference data products, ontologies, taxonomies, and semantic frameworks
Domain
Biotechnology / Pharma / Semantic Web / Knowledge Graphs
Deliverable
production ML models | product features | dashboards & analysis | research | client delivery | infrastructure
Required skills
Reference data lifecycle management, Semantic Web technologies (RDF, OWL, SKOS, SPARQL, SHACL), Graph databases (GraphDB, TopBraid, MarkLogic, Stardog), Pharma domain CVs (CDISC, MedDRA, SNOMED CT, ICD), Metadata management, FAIR Data Principles, SQL, PySpark, ETL, REST APIs, Git, JSON, XML
Preferred skills
Databricks experience, AWS cloud engineering, Agile delivery models, Knowledge graph and AI/ML initiatives exposure
Technologies
RDF, OWL, SKOS, SPARQL, SHACL, Linked Data, JSON-LD, GraphDB, TopBraid, CenTree, MarkLogic, Protégé, Semaphore, Databricks, SQL, PySpark, ETL, Git, REST APIs, XML, JSON
Responsibilities
Define and operationalize federated governance model for Reference Data; Manage ontology lifecycle activities including modeling, validation, versioning, and publishing; Develop and optimize RDF/OWL/SKOS-based semantic frameworks and SPARQL/SQL queries; Troubleshoot semantic data load and mapping issues across Semantic Layer, CDL, and graph platforms; Collaborate with domain experts to elicit, structure and formalize knowledge to build CVs, taxonomies, and ontologies; Support enterprise Data Foundations, Knowledge Graph and Metadata Management initiatives.
Seniority
Senior, hands-on IC