Graph Database Architect/Lead

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 :

1. Product, component, and device hierarchies

2. Regulatory submissions and requirements

3. Clinical, quality, and post-market data relationships

4. Data lineage, traceability, and impact analysis

- Architect and implement solutions using technologies such as :

1. Neo4j, Amazon Neptune, TigerGraph, JanusGraph, or similar

2. Ensure high performance, scalability, security, and availability of graph platforms

- Life Sciences & Medical Device Domain

- Develop graph solutions supporting :

1. Regulatory submissions and change impact analysis

2. Clinical trials and evidence management

3. Quality systems (QMS, CAPA, complaints, audits)

4. Manufacturing traceability and device history records

5. 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