Graph Engineer: Neo4j, Python, Cloud (Remote)

Cognizant; Chicago (IL); Remote; USD 88,000 - 135,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

401(k)

Paid time off

Disability insurance

Parental leave

Employee stock purchase plan

Job summary

Cognizant is seeking a Graph Engineer to design graph data models and build ETL pipelines in Python for pharma R&D data. You will develop Cypher queries, manage Neo4j deployments on cloud platforms, and enable knowledge discovery for scientists and clinical teams.

You'll collaborate across data scientists and R&D stakeholders to translate domain needs into scalable graph schemas while ensuring data quality, lineage, and regulatory compliance.

Qualifications

• 3–4 years hands-on Neo4j experience with schema design and Cypher
• Strong Python skills for ETL, data pipelines, and API development
• Experience with at least one major cloud platform (AWS, Azure, or GCP) and data governance awareness

Responsibilities

• Design graph data models spanning drug discovery pipelines and clinical documentation
• Build and maintain Python ETL/ELT pipelines ingesting data into Neo4j
• Develop and optimize Cypher queries and APIs for search and knowledge discovery
• Support entity resolution across data sources to create a unified knowledge graph
• Deploy and manage graph infrastructure on cloud platforms and manage access controls
• Collaborate with data scientists, clinical teams, and R&D researchers to translate requirements
• Ensure data quality, lineage, and regulatory compliance for audit readiness

Skills

Neo4j experience

Python

Cloud platforms

Data modeling

Git

Education

Bachelor's degree in CS/BI/DE or related field

Tools

neo4j-driver

py2neo

FastAPI/Flask

Job description

Cognizant is seeking a Graph Engineer to design graph data models and build ETL pipelines in Python for pharma R&D data. You will develop Cypher queries, manage Neo4j deployments on cloud platforms, and enable knowledge discovery for scientists and clinical teams.

You'll collaborate across data scientists and R&D stakeholders to translate domain needs into scalable graph schemas while ensuring data quality, lineage, and regulatory compliance.