Senior Data Engineer 2 at Quantiphi

Job description

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth. If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi! About Quantiphi 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. For more details, visit: Website or LinkedIn Page. Role: Senior Knowledge Graph Engineer 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 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. 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! If you like wild growth and working with happy, enthusiastic over-achievers, you ll enjoy your career with us !

Requirements

Must-haves

If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
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 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.
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.
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.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aiawspythonjavaci/cdml

Platform: workday
Effort: long