Senior Ontology and Knowledge Engineer

Vizient•Chicago, IL

2d•$102,400 - $179,000

About The Position

In this role, you will develop and maintain semantic ontologies and models that establish consistent business meaning and enable high-quality, interoperable data across the organization. You will translate business and data concepts into scalable semantic models, support knowledge graph development and integration, and collaborate with product, data, and business clients to ensure semantic assets are documented, governed, validated, and production-ready. You will contribute to the semantic foundation that enables advanced analytics, data products, and AI-enabled solutions.

Requirements

5 or more years of relevant experience required.
Hands-on knowledge of Semantic Web standards and technologies, including RDF, OWL, SKOS, SPARQL, and SHACL.
Experience with graph databases and/or triplestores, including semantic modeling, schema design, and query performance considerations in production environments.
Experience integrating disparate datasets through common vocabularies, semantic-to-data mapping, and validation.
Proficiency with ontology development tools and workflows such as Protégé, TopBraid, PoolParty, Stardog, or similar technologies.
Experience applying foundational or top-level ontologies and standards such as BFO, DOLCE, Common Core Ontologies, OBO Foundry, or similar frameworks to enterprise needs.
Working knowledge of Python, Java, or similar programming languages to support automation, testing, and semantic pipeline integration.
Experience applying software engineering practices to semantic assets, including Git-based version control, review workflows, automated validation and testing, and CI/CD release practices.
Strong analytical, problem-solving, and communication skills, with the ability to explain complex semantic concepts clearly to technical and non-technical clients.

Nice To Haves

Relevant degree preferred.

Responsibilities

Design, develop, and maintain logical, extensible ontologies, vocabularies, and semantic models aligned with enterprise concepts and analytics and AI needs.
Translate client use cases into competency questions, semantic requirements, definitions, relationships, and implementable semantic models.
Collaborate with subject matter experts and technical teams to refine concepts, relationships, modeling patterns, and semantic standards.
Support knowledge graph development and integration with enterprise data platforms, including semantic-to-data mapping, graph and triplestore implementation, and SPARQL query development.
Perform logical validation, constraint checks, and quality controls to maintain the accuracy, consistency, and interoperability of semantic assets.
Manage ontology and semantic model changes through established version control, review, testing, documentation, and release practices.
Develop and maintain ontology documentation, modeling patterns, standards, and usage guidance for technical and non-technical audiences.
Partner with data engineering, platform, product, analytics, and AI teams to align knowledge representation with enterprise data systems and implementation requirements.
Apply foundational and top-level ontologies and industry standards to enterprise use cases while balancing scalability, extensibility, and usability.
Develop automation, testing, and semantic pipeline integrations using scripting, programming, and software engineering practices.