Microsoft Fabric Ontology Engineer
Location: Chicago, ILContract Looking for 13+ year exp. RequirementsKey ResponsibilitiesDesign and maintain enterprise ontologies and knowledge graphs aligned to business domains (finance, HR, supply chain, etc.) within Microsoft FabricBuild and manage semantic models in Power BI using ontology-driven design principles, including entity hierarchies, relationships, and synonym mappingsDefine and enforce data definitions, business glossaries, and metadata standards across the Fabric lakehouse and warehouse layersCollaborate with data engineers to map ontological concepts to OneLake, Fabric Lakehouses, and Delta Lake tablesIntegrate ontologies with Microsoft Purview for data cataloguing, lineage tracking, and governanceDevelop domain-specific ontologies using standards such as OWL, RDFS, and SKOS, and expose them through Fabric APIs or semantic endpointsEnable natural language Q&A and Copilot experiences in Power BI by enriching semantic models with ontological metadataWork with AI/ML teams to provide structured ontological features for Azure OpenAI and Fabric's AI workloadsEstablish best practices and documentation for ontology lifecycle management — versioning, deprecation, and change governanceCollaborate with business stakeholders to capture and formalise domain knowledge into machine-readable modelsRequired Skills & ExperienceMicrosoft Fabric & Power BIHands-on experience with Microsoft Fabric (Lakehouse, Warehouse, Data Factory, Notebooks, Semantic Models)Strong proficiency in Power BI semantic modelling — DAX, relationships, hierarchies, calculation groupsExperience with OneLake and Delta Lake table formatsFamiliarity with Microsoft Purview for data cataloguing and lineageOntology & Knowledge EngineeringProficiency in ontology languages: OWL (Web Ontology Language), RDFS, SKOSExperience with ontology development tools such as Protégé, TopBraid Composer, or similarUnderstanding of RDF (Resource Description Framework) and SPARQL for querying knowledge graphsAbility to design taxonomies, thesauri, and controlled vocabulariesKnowledge of linked data principles and URI-based entity identificationData & Analytics EngineeringStrong SQL skills across T-SQL and Spark SQLExperience with Python or PySpark for data transformation and ontology integration pipelinesFamiliarity with REST APIs and JSON-LD for publishing and consuming semantic dataUnderstanding of medallion architecture (Bronze / Silver / Gold) within a lakehouse contextAI & Semantic TechnologiesAwareness of how ontologies enhance LLM-based applications (RAG pipelines, grounding, entity disambiguation)Experience or interest in integrating ontologies with Azure OpenAI Service or Microsoft Copilot StudioFamiliarity with knowledge graph platforms (e.g. Azure Cosmos DB, Neo4j, or AWS Neptune) is a plusPreferred QualificationsExperience with industry-standard ontologies such as FIBO (finance), HL7 FHIR (healthcare), GS1 (retail), or PROV-O (provenance)Background in enterprise data governance or MDM (Master Data Management)Microsoft certifications: DP-600 (Fabric Analytics Engineer), PL-300 (Power BI), or SC-400 (Information Protection)Degree in Computer Science, Information Science, Knowledge Engineering, or a related field