Senior Knowledge Graph Engineer — Remote (Healthcare)

Quantiphi

United States

Remote

USD 120,000 - 180,000

Full time

7 days ago
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Job summary

Quantiphi is seeking a Senior Knowledge Graph Engineer to design, build, and productionize knowledge graph solutions for healthcare data. The role focuses on translating ontology and mapping specifications into scalable graph implementations using LPG and RDF approaches.

You will work with ontology, terminology, FHIR, and data engineering teams to deliver robust mapping, data transformation, provenance, and quality controls across production pipelines.

Qualifications

  • 5+ years of software/data engineering experience with graphs.
  • Strong knowledge of graph data modeling concepts.
  • Hands-on with LPG or RDF/semantic graph technologies.
  • Experience building production data pipelines for graphs.
  • Ability to translate conceptual models into production code.

Responsibilities

  • Design, build, and productionize knowledge graph solutions.
  • Transform healthcare/FHIR data into graph representations.
  • Implement mappings between data and clinical ontology concepts.
  • Develop reusable mapping and transformation patterns.
  • Ensure provenance, identity, and data quality throughout graphs.
  • Develop and optimize graph queries using Cypher or SPARQL.
  • Collaborate with ontology, FHIR, terminology, and data teams.

Skills

Software/data eng experience
Knowledge graph concepts
LPG and RDF familiarity
Graph databases / SPARQL
Python, Java or similar
Data ingestion pipelines
Ontology mapping & provenance
Cross-functional collaboration

Tools

Neo4j/Cypher
RDF/OWL/SPARQL
SHACL validation

Job description

Quantiphi is seeking a Senior Knowledge Graph Engineer to design, build, and productionize knowledge graph solutions for healthcare data. The role focuses on translating ontology and mapping specifications into scalable graph implementations using LPG and RDF approaches.

You will work with ontology, terminology, FHIR, and data engineering teams to deliver robust mapping, data transformation, provenance, and quality controls across production pipelines.

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