Semantic Data Modeler

Job description :

We are seeking a highly skilled Semantic Data Modeler to join our data and AI team. This role will focus on designing and implementing canonical models, ontologies, and taxonomies to enable a unified semantic layer that bridges structured data from multiple silos (RDBMS and other sources) into AI-ready, knowledge-driven assets. The ideal candidate will bring expertise in both traditional data modeling (SQL, ER modeling) and semantic / knowledge representation (ontologies, RDF, OWL, SKOS), along with hands-on experience in leading ontology and taxonomy management tools.

Key Responsibilities

• Design, develop, and maintain ontologies, taxonomies, and knowledge graphs to support enterprise-wide semantic data integration.
• Build a semantic abstraction layer that maps and harmonizes relational data (SQL / RDBMS) into AI-ready semantic structures.
• Define and govern canonical data vocabularies across domains to ensure consistency, interoperability, and reuse.
• Collaborate with data engineers, data scientists, and business stakeholders to model concepts that align with business needs and AI / ML initiatives.
• Leverage ontology and taxonomy management tools (e.g., TopBraid Composer, PoolParty, Protégé, VocBench) for design, validation, and publishing.
• Develop mapping strategies from ER models / logical data models to RDF / OWL-based ontologies leveraging Linked Data Modelling Language.
• Ensure models adhere to semantic standards (RDF, OWL, SKOS, SHACL, SPARQL) and align with Unified enterprise architecture principles.
• Support data cataloging, metadata enrichment, and semantic search through ontology-driven approaches.
• Contribute to the organization's strategy of 'model once, leverage everywhere' for data standardization and AI readiness.

Experience & Qualifications & Skills

Skills Required

Sparql, owl, Sql, Rdf, ontologies