Data Ontologist

We are seeking a skilled Data Ontologist to develop and manage enterprise ontologies and semantic data models that support data governance, analytics, AI, and knowledge management initiatives. The ideal candidate will collaborate with business stakeholders, data architects, data scientists, and engineers to create semantic frameworks that improve data interoperability, quality, discoverability, and business understanding.

1. Design, develop, and maintain enterprise ontologies, taxonomies, controlled vocabularies, and knowledge graphs.
2. Define entity relationships, metadata standards, and semantic models across multiple business domains.
3. Collaborate with business and technical teams to translate business concepts into semantic data structures.
4. Support data governance initiatives by establishing data definitions, standards, and lineage frameworks.
5. Develop and maintain ontology documentation, naming conventions, and business glossaries.
6. Implement semantic technologies such as RDF, OWL, SKOS, SPARQL, and graph databases.
7. Partner with data engineers and architects to integrate ontology models with enterprise data platforms.
8. Improve data discoverability, interoperability, and reuse across systems.
9. Support AI, machine learning, and generative AI initiatives through semantic enrichment and knowledge graph development.
10. Conduct ontology reviews, impact assessments, and change management activities.
11. Ensure compliance with data governance, privacy, and regulatory requirements.

Technical Skills

1. Semantic Web Technologies
2. Knowledge Graph Design
3. SQL
4. Python
5. Data Modeling
6. Metadata Management
7. Graph Databases
8. Data Governance
9. Machine Learning Concepts
10. Cloud Data Platforms

Key Competencies

1. Analytical Thinking
2. Problem Solving
3. Attention to Detail
4. Data Governance Mindset
5. Cross-Functional Collaboration
6. Communication and Documentation
7. Strategic Thinking

Preferred Qualifications

1. Master's degree in Information Science, Data Science, Artificial Intelligence, or a related discipline.
2. Experience with enterprise data platforms such as Azure, AWS, or Google Cloud.
3. Familiarity with healthcare, finance, retail, or insurance data domains.
4. Understanding of Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
5. Knowledge of data catalog and governance tools such as Collibra, Alation, Informatica, or Microsoft Purview.
6. Strong understanding of:
1. Ontologies and taxonomy design
2. Knowledge graphs
3. Data modeling concepts
4. Metadata management
5. Master Data Management (MDM)
6. Data governance frameworks
7. Experience with any one of:
1. RDF
2. OWL
3. SPARQL
4. SKOS
5. Protg
6. Graph databases (Neo4j, Amazon Neptune, Stardog, GraphDB)
8. SQL and data analysis experience.

Strong communication and stakeholder management skills