Data Modeler - Ontology

It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business. Job Description About the Role We are looking for a hands-on Ontology / Knowledge Graph Engineer who understands not just graph databases, but the true semantic foundations behind enterprise knowledge graphs. This role requires experience in building domain ontologies, modeling conceptual semantics, and connecting those models to enterprise data sources. This is not a Cypher-only graph querying role. This is a role for someone who has worked with OWL/RDF, domain modeling, and semantic standards—and can translate complex insurance concepts into a formal ontology that powers AI, LLMs, data governance, and enterprise knowledge systems. Key Responsibilities 1. Ontology Design & Semantic Modeling Design, model, and maintain insurance domain ontologies using OWL/RDF. Build conceptual and logical semantic models for entities such as:Policies, Coverages, Perils, Claims, Loss Events, Parties, Risk Objects, Brokers/Agents. Define canonical data definitions, taxonomies, hierarchical relationships, and semantic constraints. Translate business domain models and regulatory structures into formal semantic structures. 2. Knowledge Graph Architecture Design and extend production-grade knowledge graphs derived from ontologies. Make design decisions on:How the ontology becomes the semantic index for enterprise data. How graph nodes point back to source systems through schema mapping. How the KG will be used in RAG, LLM context grounding, or reasoning pipelines. Implement ontology-driven schemas using RDF stores or labeled-property graph stores. 3. Source System Mapping Parse schemas from policy admin, claims, CRM, billing, and underwriting systems. Map source fields to ontology entities using:Schema parsing Semantic mapping Transformation rules Ensure semantic alignment and consistency across diverse insurance systems. 4. Azure Cloud Integration Deploy and operationalize ontology and KG components using:Azure Data Lake / Storage Azure Purview / Microsoft Fabric Catalog Azure Cognitive Search (for semantic indexing) Azure Kubernetes Services / Azure Functions (for KG pipelines) Azure OpenAI (for semantic enrichment, RAG, and reasoning) Integrate KG metadata into Azure metadata and lineage systems. 5. Collaboration & Governance Work closely with:Underwriting SMEs Claims SMEs Data governance teams Data engineering teams AI/ML product teams Document semantic models, maintain change logs, and drive ontology versioning. Required Skills (Non-Negotiable) Hands-on experience in ontology development, not just graph querying. Strong knowledge of:OWL, RDF, RDFS, SKOS SPARQL, SHACL (preferred) Experience designing conceptual and logical domain models. Demonstrated ability to build a knowledge graph from scratch, not just use one. Strong insurance domain understanding:Policy structures Exposure / risk modeling fundamentals