Data Governance Context Engineer

We are seeking a Data Governance Context Engineer to design, evolve, and operationalize semantic models and knowledge graphs that improve data understanding and reuse across the organization. This is a hands-on individual contributor role focused on ontology design, semantic consistency, and collaboration with business and technology partners. You will work closely with subject matter experts and data teams to translate real-world business concepts into well-structured semantic models that support analytics, AI, and data integration use cases. This role is well-suited for a senior practitioner with a strong foundation in semantic technologies who enjoys working at the intersection of data, meaning, and business context.

What you'll do in the role:

• Partner with business subject matter experts to understand data domains and capture key concepts, relationships, and definitions.
• Design, maintain, and evolve ontologies, taxonomies, and semantic models aligned to real-world business processes.
• Build and manage knowledge graphs that standardize meaning across datasets and systems.
• Develop and maintain RDF-based representations and semantic relationships using established semantic web standards.
• Ensure semantic models remain consistent, extensible, and understandable as business needs evolve.
• Collaborate with data and platform teams to integrate semantic models into data platforms, while publishing and documenting reusable semantic artifacts and best practices
• Familiarity with Python and AI

What you'll bring to the role:

• 6+ years of professional experience with hands-on work in semantic modeling, knowledge graphs, or ontology development.
• Practical experience designing and applying ontologies or semantic models in real-world data environments.
• Working knowledge of semantic web technologies (e.g., RDF, RDFS, OWL) and modeling complex data relationships.
• Experience with Knowledge Graph platforms and tooling (e.g., Neo4j) and modern graph-enabled AI approaches such as GraphRAG is a strong plus.
• Ability to translate business concepts into structured semantic representations.
• Familiarity with Python for data work, automation, or supporting semantic workflows.
• Strong communication skills, comfort collaborating with technical and non-technical partners, and a Bachelor’s degree or equivalent practical experience.

Exposure to one or more of the following areas is a plus:

Collibra or other AI/ML DQ solutions Data Stewardship, metadata management, data lineage, and master data management Business intelligence tools and automation platforms