Ontology Engineer

Novartis Pharmaceuticals Corporation•East Hanover, NJ

1d•Hybrid

About The Position

We are hiring a Senior Semantic Engineer / Ontology Engineer to lead the design of healthcare-grade ontologies and semantic layers that power trusted analytics, interoperable data products, and AI-ready knowledge systems. You will apply metrics-first semantic modeling and ontology engineering practices aligned to the principles such as clear semantics, reusable meaning, governance-by-design, and measurable business outcomes. You’ll work across RDF and property graph paradigms and Snowflake semantic layer.

Requirements

8+ years in semantic engineering, ontology engineering, knowledge graph development, or closely related roles.
Demonstrated experience in healthcare data domains (payer/provider, clinical, claims, RWE, quality, outcomes, etc.).
Strong hands-on ontology engineering experience: RDF, RDFS, OWL
SPARQL and/or graph query experience
Ontology modularization, alignment, and lifecycle management
Experience with property graph modeling (e.g., Neo4j-style patterns) and translating between RDF and property graph representations when needed.
Proven delivery of a metrics-first approach: Canonical KPIs/metrics definitions, dimensional modeling alignment, semantic consistency across BI and data products.
Experience working with modern cloud data platforms, especially Snowflake, and exposure to Snowflake Cortex for AI-enabled workflows.
Strong stakeholder communication skills: able to translate clinical/business intent into precise semantic definitions and usable artifacts.

Nice To Haves

Familiarity with healthcare interoperability and terminology standards (e.g., HL7/FHIR, SNOMED CT, LOINC, ICD-10) and how to map/align them to enterprise semantics.
Experience with semantic tooling and practices, validation rules, ontology testing, and CI/CD for semantic assets.
Experience deploying semantic context layers

Responsibilities

Design and evolve healthcare ontologies and semantic models to standardize meaning across domains (clinical, patient, provider, claims, access, quality, outcomes).
Design data products that are AI-ready and leverage ontologies and semantic models
Build metrics-first semantic layers:
Define canonical metric definitions, dimensions, hierarchies, and calculation rules.
Ensure metrics are explainable, auditable, and consistently implemented across products and teams.
Model knowledge in both: RDF (RDFS/OWL) for formal semantics and interoperability. Property graphs for traversal-heavy use cases and relationship analytics.
Develop and maintain semantic artifacts: Concept schemes, entity models, vocabularies, mappings, and documentation.
Alignment patterns between ontologies, data products, and downstream analytics/AI use cases.
Implement semantic integration patterns: Entity identity resolution, entity linking, terminology harmonization, and enrichment workflows.
Partner with platform teams to operationalize semantics in Snowflake: Enable semantic access patterns that support analytics and AI applications.
Contribute to solutions that leverage Snowflake Cortex for semantic enrichment and assisted discovery (within established governance constraints).
Collaborate with governance and architecture stakeholders to embed: Versioning, stewardship workflows, quality checks, and change management for semantic assets.
Guide best practices and mentor engineers/analysts on ontology engineering, graph modeling, and metrics-first design.