Graph Engineer (Neo4j, Python, Cloud)

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

Job Title – Graph Engineer (Neo4j, Python, Cloud)

*Please note this role is not able to offer visa transfer or sponsorship now or in the future*

About the Role

We're looking for a Graph Engineer to join our Data & Knowledge Engineering team supporting Pharma R&D initiatives spanning drug discovery and clinical documentation. You'll design, build, and maintain graph-based data models that connect scientific, experimental, and regulatory data — enabling researchers and scientists to uncover relationships across compounds, targets, trials, and documents that traditional relational systems struggle to surface.

In this role, you will:

1. Design and implement graph data models that represent entities and relationships across drug discovery pipelines (targets, compounds, assays, pathways) and clinical documentation (trials, protocols, adverse events, regulatory submissions).
2. Build and maintain ETL/ELT pipelines in Python to ingest structured and unstructured data from source systems (LIMS, ELN, clinical trial databases, document repositories) into Neo4j.
3. Develop and optimize Cypher queries and APIs that power search, recommendation, and knowledge-discovery features used by scientists and clinical documentation teams.
4. Support entity resolution and linkage across disparate data sources — connecting compounds, genes, diseases, and clinical documents into a unified knowledge graph.
5. Deploy and manage graph infrastructure on cloud platforms, including provisioning Neo4j instances (AuraDB or self-managed), monitoring performance, and managing access controls in compliance with data governance policies.
6. Collaborate with cross-functional stakeholders — data scientists, clinical documentation specialists, and R&D researchers — to translate domain requirements into scalable graph schemas and queries.
7. Ensure data quality, lineage, and compliance with pharma industry standards (GxP, HIPAA where applicable) throughout the graph data lifecycle, including documentation of data models and pipeline logic for audit readiness.

We strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a remote position open to qualified applicants in the United States. Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you’re engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.

What you need to have to be considered

• 3–4 years of hands‑on experience with Neo4j (or comparable graph database) — schema design, Cypher query writing, and performance tuning
• Strong Python skills for data pipelines, ETL, and API development (pandas, py2neo/neo4j-driver, FastAPI/Flask a plus)
• Working experience with at least one major cloud platform (AWS, Azure, or GCP) storage, compute, and managed database services
• Understanding data modeling concepts (relational‑to‑graph translation, ontology/taxonomy basics)
• Familiarity with version control (Git) and CI/CD basics
• Bachelor’s degree in computer science, Bioinformatics, Data Engineering, or related field

Salary and Other Compensation

Applications will be accepted until October 29, 2026.

The annual salary for this position is between $88,000 - $135,000 depending on experience and other qualifications of the successful candidate.

This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.

Benefits

• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long‑term/Short‑term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan

Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.