Senior Knowledge Graph Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, implement, construct, and sustain production knowledge graph solutions utilizing LPG and RDF graph technologies.

• Create scalable pipelines to convert healthcare/FHIR data into suitable graph representations.

• Implement mappings between patient/clinical data and the concepts depicted in the clinical ontology.

• Develop reusable mapping and transformation patterns instead of one-time solutions.

• Establish consistent methodologies for entity identity, canonical identifiers/URI/IRI, relationships, and concept linking.

• Ensure provenance and traceability between original data, mapping rules, and the resultant graph entities and relationships.

• Develop and enhance graph queries using Cypher and/or SPARQL.

• Set up automated validation and testing processes to detect unresolved mappings, inconsistent relationships, and other graph quality concerns.

• Collaborate with ontology, FHIR, terminology, and clinical subject matter experts (SMEs) to clarify ambiguous or missing mapping requirements.

• Engage in technical design, architecture reviews, code evaluations, and adhere to engineering best practices.

⛳️ Requirements

• Over 5 years of experience in software/data engineering, including practical experience with knowledge graphs or graph technologies.

• Strong comprehension of knowledge graph and graph data modeling principles.

• Practical experience with Labeled Property Graphs, such as Neo4j/Cypher or similar, or RDF/semantic technologies like RDF/RDFS, OWL, and SPARQL.

• Working knowledge of, or capability to work across, both LPG and RDF graph models.

• Proficient programming skills in Python, Java, or comparable languages.

• Experience in developing production data ingestion, transformation, or integration pipelines.

• Familiarity with graph databases and/or RDF triple stores.

• Understanding of entity identity, graph relationships, mappings, provenance, and data quality.

• Capability to translate conceptual models and mapping specifications into production implementations.

• Ability to effectively navigate evolving requirements and collaborate with cross-functional technical/domain teams.

• Hands-on experience with both LPG and RDF/semantic knowledge graphs.

• Experience in healthcare or life sciences data.

• Knowledge of HL7 FHIR, including Coding, CodeableConcept, Reference, and Identifier.

• Experience with ontology-driven data integration or semantic mapping.

• Familiarity with SHACL or other graph/semantic validation methods.

• Experience with terminology/concept normalization and canonical concept mapping.

• Familiarity with clinical terminologies such as SNOMED CT, LOINC, RxNorm, ICD, or UMLS.

• Experience with cloud technologies and CI/CD practices.

🏝️ Benefits

• Opportunities for upskilling and professional development.

• Exposure to AI, ML, data, and cloud technologies.

• Opportunities to collaborate with Fortune 1000 companies.

• Work within a research-driven organization with over 60 patents filed.

• Collaboration with skilled colleagues.

• Remote work options available.

• Up to 25% travel to client sites throughout the US.