Senior Data Engineer

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

📋 Description

• Design, develop, and operationalize knowledge graph solutions for healthcare and clinical data.

• Create, implement, and manage production knowledge graph solutions utilizing LPG and RDF graph technologies.

• Construct scalable pipelines that convert healthcare/FHIR data into suitable graph representations.

• Establish mappings between patient/clinical data and concepts represented within the clinical ontology.

• Create reusable mapping and transformation patterns.

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

• Ensure 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 graph quality issues.

• Collaborate with teams specializing in ontology, terminology, FHIR, clinical/domain, and data engineering.

• Resolve ambiguous or missing mapping requirements in consultation with subject matter experts.

• Engage in technical design, architecture reviews, code reviews, and uphold engineering best practices.

⛳️ Requirements

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

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

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

• Proficient working knowledge of both LPG and RDF graph models.

• Strong programming expertise in Python, Java, or comparable languages.

• Experience in building 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.

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

• Capability to work effectively with evolving requirements and 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 in 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 processes.

🏝️ Benefits

• Opportunities for upskilling and professional development.

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

• Chance to collaborate with Fortune 1000 companies.

• Research-driven work environment.

• Opportunity to work alongside passionate, talented colleagues.

• Collaborate with disruptive innovators.

• Flexible remote work arrangements.

• Travel opportunities to client locations across the US.