Senior Knowledge Graph Engineer

Quantiphi

4d • Remote

About The Position

Quantiphi is seeking a Senior Knowledge Graph Engineer to design, build, and productionize knowledge graph solutions for healthcare and clinical data. The architecture combines a Labeled Property Graph (LPG) for patient and clinical data with an RDF-based graph for clinical ontology and semantic knowledge. The role translates ontology and mapping specifications into scalable graph solutions, including data transformation, graph ingestion, concept and entity linking, provenance, validation, and querying. The engineer works with ontology, terminology, FHIR, clinical/domain, and data engineering teams to implement agreed semantic and mapping decisions.

Requirements

• At least 5 years of software or 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 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.
• Strong programming skills in Python, Java, or similar languages.
• Experience building production data ingestion, transformation, or integration pipelines.
• Experience with graph databases and/or RDF triple stores.
• Understanding of entity identity, graph relationships, mappings, provenance, and data quality.
• Ability to translate conceptual models and mapping specifications into production implementations.
• Ability to work effectively with evolving requirements and cross-functional technical and domain teams.

Nice To Haves

• Hands-on experience with both LPG and RDF/semantic knowledge graphs.
• Healthcare or life sciences data experience.
• Familiarity with HL7 FHIR, including Coding, CodeableConcept, Reference, and Identifier.
• Experience with ontology-driven data integration or semantic mapping.
• Experience with SHACL or other graph/semantic validation approaches.
• Experience with terminology/concept normalization and canonical concept mapping.
• Familiarity with clinical terminologies such as SNOMED CT, LOINC, RxNorm, ICD, or UMLS.
• Cloud and CI/CD experience.

Responsibilities

• Develop, implement, build, and maintain production knowledge graph solutions using LPG and RDF graph technologies.
• Build scalable pipelines to transform healthcare and FHIR data into graph representations.
• Implement mappings between patient and 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.
• Work with ontology, FHIR, terminology, and clinical subject-matter experts to clarify ambiguous or missing mapping requirements.
• Participate in technical design, architecture reviews, code reviews, and engineering best practices.

Benefits

• Opportunities to upskill and develop professionally while solving complex technology challenges.
• Exposure to AI, machine learning, data, and cloud technologies and work with Fortune 1000 companies.
• Opportunity to work in a research-focused organization with 60+ patents filed across various disciplines.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed