Senior Knowledge Graph Engineer

Ladders; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

Our client seeks a Senior Knowledge Graph Engineer to design and maintain production knowledge graph solutions, turning healthcare data into scalable graph structures. You will build ingestion and transformation pipelines with provenance and data quality in mind, using both property graph and RDF approaches.

Remote work is available, with focus on graph modeling depth, Cypher and SPARQL queries, and collaboration with cross-functional teams to deliver reliable graph-based solutions for

Qualifications

• 5+ years of software or data engineering experience with knowledge graphs or graph tech.

Responsibilities

• Develop, implement, and maintain production knowledge graph solutions using Labeled Property Graph and RDF technologies.

Skills

Graph data modeling

Neo4j/Cypher

RDF/OWL/SPARQL

Python

Java

Data pipelines

Provenance & data quality

Tools

Neo4j

Job description

For our client, we are seeking a Senior Knowledge Graph Engineer to join the team of a leader in the Information Technology space.

This role will focus on designing and maintaining production knowledge graph solutions that turn complex healthcare data into scalable, usable graph structures. You will partner with technical teams to build reliable ingestion and transformation pipelines, strengthen data relationships and provenance, and optimize graph performance for downstream use cases. The work requires strong depth in graph modeling and the ability to apply both property graph and RDF approaches in a production environment.

Location: Remote

Responsibilities

• Develop, implement, and maintain production knowledge graph solutions using Labeled Property Graph and RDF technologies.
• Build scalable pipelines to transform healthcare and FHIR data into graph representations.
• Implement mappings between patient and clinical data and clinical ontology concepts.
• Develop reusable mapping and transformation patterns for efficiency.
• Ensure consistent approaches for entity identity, canonical identifiers, and concept linking.
• Maintain provenance and traceability between source data and resulting graph entities.
• Optimize graph queries using Cypher and/or SPARQL.

Qualifications

• 5+ years of software or data engineering experience, particularly 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 RDF and semantic technologies such as RDF/RDFS, OWL, and SPARQL.
• Working knowledge of both Labeled Property Graph and RDF graph models.
• Strong programming skills in Python, Java, or similar languages.
• Experience building production data ingestion, transformation, or integration pipelines.
• Understanding of entity identity, graph relationships, mappings, provenance, and data quality.

Benefits

• Make an impact at a rapidly growing AI-first digital engineering company.
• Upskill and tackle complex challenges in cutting-edge technology.
• Work in an innovative environment with a focus on research and development.
• Gain exposure to breakthrough AI, ML, data, and cloud technologies with Fortune 1000 companies.
• Join a culture of growth and collaboration with enthusiastic colleagues.

Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.