Data Ontology Engineer

General Dynamics is a leading company in the defense and scientific sectors, known for its innovative solutions. They are seeking a Data Ontology Engineer to design and maintain semantic schemas, implement knowledge graphs, and integrate heterogeneous data sources into a common vocabulary to support AI systems.

Responsibilities:

• Domain ontologies. Design and maintain semantic schemas that describe key engineering and manufacturing entities — products, BOMs, plants, equipment, processes, work orders — and their relationships across systems
• Knowledge graphs. Implement ontologies using semantic web or graph technologies (RDF/OWL/SHACL/SPARQL or property-graph equivalents like Neo4j). Build, query, validate, and tune knowledge graphs in production
• Data alignment. Integrate heterogeneous data sources — PLM, ERP, MES, CMMS, QMS, data lakes — into a common vocabulary. Align schemas, code sets, and master data to the ontology so AI services see one coherent picture
• Semantic layer. Design the enterprise semantic layer that BI tools, analytics platforms, and AI/LLM applications query consistently. Define core business entities, metrics, and hierarchies and map them to existing data stores
• Ontology governance. Manage versioning, documentation, reuse of industry standards, and enforcement of modeling best practices across pods. Your ontologies are shared assets — they must be maintainable by others

Requirements:

• Bachelor's degree in Computer Science, Data Science, Information Science, or a related field, plus 5 years of experience; or Master's degree plus 3 years of experience
• Hands-on experience with knowledge graph or ontology technologies — RDF/OWL/SHACL/SKOS, SPARQL, and/or graph databases (Neo4j, Stardog, Ontotext, AWS Neptune, or similar)
• Experience integrating disparate enterprise data sources into a shared vocabulary or knowledge graph — you have aligned data across systems that use different schemas, code sets, and terminology
• Strong data modeling skills — dimensional modeling, semantic modeling, or formal ontology design applied in production, not just academic settings
• Experience with enterprise data platforms — data warehouses, data lakes, Snowflake, Palantir Foundry, or similar
• U.S. citizenship required. Department of Defense Secret security clearance is required at time of hire
• Experience building semantic layers or metrics layers consumed by BI, analytics, or AI/LLM applications
• Experience with enterprise systems data (ERP, MES, PLM, CRM) — you understand the data structures these systems produce
• Familiarity with AI/ML data requirements — embeddings, vectorization, retrieval-augmented generation, and how knowledge graphs support LLM reasoning
• Comfortable leading workshops with non-technical business SMEs to capture requirements and iteratively refine data models
• Experience with ontology governance — versioning, documentation, standards reuse across teams or an enterprise