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, Protg, 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
- Bachelor's or master's degree in computer science, Information Systems, Data Science or related field.
- 5-8 Years of total experience in data modeling or information architecture or Data engineering.
- Minimum 3+ years of hands-on experience in ontology/taxonomy development and semantic technologies.
- Practical experience in ontology engineering tools such as: TopBraid Composer, PoolParty, Protg (or similar)
- Strong background in SQL, relational data modeling, and ER modeling.
- Proven expertise in ontology engineering and taxonomy development using RDF, OWL, SKOS.
- Solid understanding of semantic technologies (SPARQL, SHACL, R2RML, Knowledge Graphs).
- Experience integrating relational data/schemas into semantic/Knowledge graphs
- Familiarity with data integration patterns, metadata management, and data catalogs.
- Excellent problem-solving, communication, and collaboration skills.
- Nice to Have: Python, RML/R2RML Mappings, Linked Data modelling Language or other modeling frameworks
