Job Title: Graph Database Architect / Lead Knowledge Graph Engineer
Location: Remote
Experience: 15+ Years
About the Role
We are looking for a highly experienced Graph Database Architect / Lead Knowledge Graph Engineer to design and deliver enterprise-grade graph solutions. This role requires deep expertise in graph databases, knowledge graph engineering, and strong domain experience in life sciences and medical devices.
You will play a critical role in building scalable graph architectures to support regulatory intelligence, clinical data integration, product traceability, and compliance analytics in highly regulated environments.
Key Responsibilities
Graph & Knowledge Graph Architecture
- Define and lead the enterprise graph and knowledge graph strategy
- Design scalable graph models for:
- Product, component, and device hierarchies
- Regulatory submissions and requirements
- Clinical, quality, and post-market data relationships
- Data lineage, traceability, and impact analysis
- Architect and implement solutions using technologies such as:
- Neo4j, Amazon Neptune, TigerGraph, JanusGraph, or similar
- Ensure high performance, scalability, security, and availability of graph platforms
Life Sciences & Medical Device Domain
- Develop graph solutions supporting:
- Regulatory submissions and change impact analysis
- Clinical trials and evidence management
- Quality systems (QMS, CAPA, complaints, audits)
- Manufacturing traceability and device history records
- Post-market surveillance and vigilance reporting
- Model relationships across structured and unstructured datasets
- Ensure alignment with global regulatory standards and compliance requirements
Regulatory & Compliance
- Ensure compliance with:
- FDA 21 CFR Part 11
- ISO 13485
- GxP (GMP, GCP, GLP)
- MDR / IVDR (EU)
- HIPAA & GDPR
Required Skills
Primary Skills
- Graph Database Architecture
- Knowledge Graph Engineering
- Life Sciences / Medical Device Domain Expertise
- Regulatory Compliance (FDA, ISO, GxP, MDR/IVDR)
Preferred Skills
- Experience with large-scale enterprise data platforms
- Strong understanding of data modeling and ontology design
- Experience with data integration and analytics frameworks
