Quantiphi

Quantiphi

Senior Knowledge Graph Engineer

USA - Remote · Senior · Full-time

Sponsorship not specifiedDetected 2 days ago
PythonJavaCode ReviewSnowflakeAWSGCPCI/CDMachine LearningData EngineeringExcelHL7/FHIRResearch

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About the role

  • Our architecture uses a hybrid graph approach, combining a Labeled Property Graph (LPG) for patient/clinical data with an RDF-based graph for clinical ontology and semantic knowledge.
  • The role will focus on translating ontology and mapping specifications into scalable graph solutions, including data transformation, graph ingestion, concept/entity linking, provenance, validation, and querying.
  • You will work closely with ontology, terminology, FHIR, clinical/domain, and data engineering teams to translate agreed semantic and mapping decisions into robust technical implementations.

Responsibilities

  • Develop, implement, build, and maintain production knowledge graph solutions across LPG and RDF graph technologies.
  • Implement mappings between patient/clinical data and concepts represented in the clinical ontology.
  • Develop reusable mapping and transformation patterns rather than one-off implementations.
  • Implement consistent approaches for entity identity, canonical identifiers/URI/IRI, relationships, and concept linking.
  • Maintain provenance and traceability between source data, mapping rules, and resulting graph entities and relationships.
  • Develop and optimize graph queries using Cypher and/or SPARQL.
  • Implement automated validation and testing to identify unresolved mappings, inconsistent relationships, and other graph-quality issues.
  • Participate in technical design, architecture reviews, code reviews, and engineering best practices.
  • We partner with enterprises to reimagine their businesses through intelligent, scalable, and transformative AI-driving measurable outcomes at the very core of their operations.

Requirements

  • 5+ years of software/data engineering experience, including hands-on experience with knowledge graphs or graph technologies.
  • Strong understanding of knowledge graph and graph data modeling concepts.
  • Hands-on experience with either: Labeled Property Graphs, such as Neo4j/Cypher or equivalent, or RDF/semantic technologies, such as RDF/RDFS, OWL, and SPARQL.
  • Working knowledge of, or ability to work across, both LPG and RDF graph models.
  • Experience with graph databases and/or RDF triple stores.
  • Ability to translate conceptual models and mapping specifications into production implementations.
  • Ability to work effectively with evolving requirements and cross-functional technical/domain teams.
  • Hands-on experience with both LPG and RDF/semantic knowledge graphs.
  • Familiarity with HL7 FHIR, including concepts such as Coding, CodeableConcept, Reference, and Identifier.
  • Experience with ontology-driven data integration or semantic mapping.

Benefits

  • We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
  • Build scalable pipelines to transform healthcare/FHIR data into appropriate graph representations.
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