Data Modeler - Ontology
Fractal (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 20–35 LPA
Posted 10h ago
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Job description
Structured overview of role & requirements
About This Role
- Design and maintain insurance domain ontologies using OWL/RDF to formalize complex insurance concepts for AI and enterprise knowledge systems.
- Build and extend production-grade knowledge graphs, architecting schema mappings from multiple insurance source systems for semantic indexing and reasoning pipelines.
- Deploy and operationalize ontology and knowledge graph components within Azure cloud services (Data Lake, Purview, Cognitive Search, OpenAI) integrating KG metadata with enterprise data governance systems.
Minimum Requirements
- Hands-on experience in ontology development, not limited to graph querying.
- Strong knowledge of OWL, RDF, RDFS, SKOS, SPARQL; SHACL preferred.
- Experience building knowledge graphs from scratch and mapping enterprise source schemas to ontologies.
- Strong understanding of insurance domain: policy structures, exposure/risk modeling, claims lifecycle, product hierarchies, regulatory constraints.
Ideal Candidate Profile
- Proven ability to translate complex insurance domain and regulatory structures into formal semantic and ontology models.
- Experience working with semantic technology stacks such as Stardog, GraphDB, Neo4j (with RDF), TopQuadrant, or AllegroGraph.
- Familiarity with LLM integration, semantic pipelines, and Azure OpenAI or similar frameworks for context engineering and RAG indexing.