Senior Knowledge Graph Engineer - Remote (Healthcare/AI)

Quantiphi

Boston (MA)

Híbrido

USD 140 000 - 180 000

Tempo integral

Há 3 dias
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Resumo da oferta

Quantiphi is seeking a Senior Knowledge Graph Engineer to design, build, and productionize knowledge graph solutions for healthcare data. You will work with LPG and RDF graphs, translating ontologies into scalable data pipelines and ensuring data provenance.

The role requires 5+ years in software/data engineering with graph technologies, Python/Java skills, and experience transforming FHIR data into graph representations. Remote US work offered.

Qualificações

  • 5+ years of software/data engineering experience with knowledge graphs or graph technologies.
  • Strong knowledge of graph data modeling concepts and LPG/RDF models.
  • Proficiency in Python or Java and building production data pipelines.
  • Experience with LPG (Neo4j/Cypher) or RDF/semantic technologies and graph databases.
  • Familiarity with HL7 FHIR concepts and clinical terminology is a plus.

Responsabilidades

  • Develop, implement, build, and maintain production knowledge graph solutions across LPG and RDF.
  • Build scalable pipelines to transform healthcare/FHIR data into graph representations.
  • Implement mappings between patient/clinical data and concepts in the ontology.
  • Develop reusable mapping patterns and ensure provenance and data quality.
  • Work with ontology, terminology, FHIR, and data engineering teams on semantic mappings.

Conhecimentos

Graph knowledge
LPG
RDF/OWL
Cypher
SPARQL
Python
Java
Data pipelines
Ontology
FHIR

Ferramentas

Neo4j/Cypher
RDF stores
SHACL
SPARQL tooling

Descrição da oferta de emprego

Quantiphi is seeking a Senior Knowledge Graph Engineer to design, build, and productionize knowledge graph solutions for healthcare data. You will work with LPG and RDF graphs, translating ontologies into scalable data pipelines and ensuring data provenance.

The role requires 5+ years in software/data engineering with graph technologies, Python/Java skills, and experience transforming FHIR data into graph representations. Remote US work offered.

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