Senior Knowledge Graph Engineer

Quantiphi; United States; Teletrabalho; USD 140 000 - 190 000; Tempo integral

Resumo da oferta

Quantiphi, an AI-first digital engineering and consulting company, is seeking a Senior Knowledge Graph Engineer to design, build, and productionize knowledge graph solutions for healthcare data. The role uses a hybrid graph approach combining LPG for patient data and RDF for ontology, translating mappings into scalable implementations.

You will collaborate with ontology, terminology, FHIR and data engineering teams, develop pipelines, ensure provenance, and optimize queries with Cypher and

Qualificações

• 5+ years of software/data engineering with knowledge graphs.
• Strong knowledge graph modeling concepts.
• Hands-on LPG and RDF technologies.
• Python or Java programming skills.
• Experience building data ingestion pipelines.
• Experience with graph databases/RDF stores.
• Understanding entity identity and provenance.
• Translate conceptual models into production code.
• Collaborate with cross-functional teams.

Responsabilidades

• Develop and maintain production knowledge graph solutions across LPG and RDF.
• Build pipelines to transform healthcare/FHIR data into graphs.
• Implement mappings between data and clinical ontology concepts.
• Develop reusable mapping and transformation patterns.
• Ensure canonical identifiers, relationships, and concept linking.
• Maintain provenance and traceability.
• Develop graph queries using Cypher and/or SPARQL.
• Implement automated validation and testing for mappings.
• Collaborate with ontology, FHIR, terminology teams.
• Participate in design reviews and best practices.

Conhecimentos

Knowledge graphs

LPG/RDF modeling

Cypher

SPARQL

Python/Java

Data pipelines

Ontology mapping

Provenance

FHIR knowledge

Healthcare data

Ferramentas

Neo4j

RDF stores

OWL

SHACL

ETL tooling

Descrição da oferta de emprego

Quantiphi is an award-winning, AI-First digital engineering and consulting company focused on delivering high-impact Services and Solutions that help organizations solve what truly matters. We partner with enterprises to reimagine their businesses through intelligent, scalable, and transformative AI—driving measurable outcomes at the very core of their operations.

Since our founding in 2013, Quantiphi has tackled some of the world’s most complex business challenges by combining deep industry expertise, disciplined cloud and data engineering practices, and cutting-edge applied AI research. Our work is rooted in delivering accelerated, quantifiable business value—not just technology for technology’s sake.

Headquartered in Boston, Quantiphi is a global organization with 4,000+ professionals serving clients across key industry verticals, including BFSI, Healthcare & Life Sciences, CPG, MFG, TME etc. As an Elite and Premier partner to leading cloud and AI platforms such as NVIDIA, Google Cloud, AWS, and Snowflake, we build and deliver enterprise‑grade AI services and solutions that create real‑world impact.

Experience: 5+ years of software/data engineering experience

Employment Type: Full-Time (US Remote)

Work Location: US Remote (Up to 25% travel to client sites across the US)

Role Overview

We are looking for a Senior Knowledge Graph Engineer to design, build, and productionize knowledge graph solutions for healthcare and clinical data.

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 semantically 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.

Key Responsibilities

• Develop, implement, build, and maintain production knowledge graph solutions across LPG and RDF graph technologies.
• Build scalable pipelines to transform healthcare/FHIR data into appropriate graph representations.
• 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.
• Work with ontology, FHIR, terminology, and clinical SMEs to clarify ambiguous or missing mapping requirements.
• Participate in technical design, architecture reviews, code reviews, and engineering best practices.

Required Qualifications

• 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.
• 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/domain teams.

Other Qualifications (OQs)

• Hands-on experience with both LPG and RDF/semantic knowledge graphs.
• Healthcare or life sciences data experience.
• Familiarity with HL7 FHIR, including concepts such as 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.

What Sets You Apart?

• Hands-on experience with both LPG and RDF/semantic knowledge graphs.
• Healthcare or life sciences data experience with familiarity with HL7 FHIR and clinical terminologies (SNOMED CT, LOINC, RxNorm, ICD, or UMLS).
• Experience with ontology-driven data integration, semantic mapping, and SHACL/semantic validation approaches.
• Cloud and CI/CD engineering experience in production environment.

What’s In It For YOU At Quantiphi?

• Make an impact at one of the world’s fastest-growing AI-first digital engineering companies.
• Upskill and discover your potential as you solve complex challenges in cutting-edge areas of technology alongside passionate, talented colleagues.
• Work where innovation happens - work with disruptive innovators in a research-focused organization with 60+ patents filed across various disciplines.
• Stay ahead of the curve, immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 1000 companies.
• If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!