Microsoft Fabric Ontology Engineer, Chicago, IL

Requirements

Key Responsibilities

• Design and maintain enterprise ontologies and knowledge graphs aligned to business domains (finance, HR, supply chain, etc.) within Microsoft Fabric
• Build and manage semantic models in Power BI using ontology-driven design principles, including entity hierarchies, relationships, and synonym mappings
• Define and enforce data definitions, business glossaries, and metadata standards across the Fabric lakehouse and warehouse layers
• Collaborate with data engineers to map ontological concepts to OneLake, Fabric Lakehouses, and Delta Lake tables
• Integrate ontologies with Microsoft Purview for data cataloguing, lineage tracking, and governance
• Develop domain-specific ontologies using standards such as OWL, RDFS, and SKOS, and expose them through Fabric APIs or semantic endpoints
• Enable natural language Q&A and Copilot experiences in Power BI by enriching semantic models with ontological metadata
• Work with AI/ML teams to provide structured ontological features for Azure OpenAI and Fabric''s AI workloads
• Establish best practices and documentation for ontology lifecycle management — versioning, deprecation, and change governance
• Collaborate with business stakeholders to capture and formalise domain knowledge into machine-readable models

Required Skills & Experience

Microsoft Fabric & Power BI

• Hands-on experience with Microsoft Fabric (Lakehouse, Warehouse, Data Factory, Notebooks, Semantic Models)
• Strong proficiency in Power BI semantic modelling — DAX, relationships, hierarchies, calculation groups
• Experience with OneLake and Delta Lake table formats
• Familiarity with Microsoft Purview for data cataloguing and lineage

Ontology & Knowledge Engineering

• Proficiency in ontology languages: OWL (Web Ontology Language), RDFS, SKOS
• Experience with ontology development tools such as Protégé, TopBraid Composer, or similar
• Understanding of RDF (Resource Description Framework) and SPARQL for querying knowledge graphs
• Ability to design taxonomies, thesauri, and controlled vocabularies
• Knowledge of linked data principles and URI-based entity identification

Data & Analytics Engineering

• Strong SQL skills across T-SQL and Spark SQL
• Experience with Python or PySpark for data transformation and ontology integration pipelines
• Familiarity with REST APIs and JSON-LD for publishing and consuming semantic data
• Understanding of medallion architecture (Bronze / Silver / Gold) within a lakehouse context

AI & Semantic Technologies

• Awareness 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 Studio
• Familiarity with knowledge graph platforms (e.g. Azure Cosmos DB, Neo4j, or AWS Neptune) is a plus

Preferred Qualifications

• Experience 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