Graph Engineer (Neo4j, Python, Cloud)

Cognizant is seeking a Graph Engineer to join its Data & Knowledge Engineering team supporting pharmaceutical research and development initiatives. The role focuses on designing graph data models, building Python-based ETL/ELT pipelines, developing Neo4j queries and APIs, managing cloud graph infrastructure, and ensuring data quality and compliance.

Responsibilities:

• 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)
• 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
• Develop and optimize Cypher queries and APIs that power search, recommendation, and knowledge-discovery features used by scientists and clinical documentation teams
• Support entity resolution and linkage across disparate data sources — connecting compounds, genes, diseases, and clinical documents into a unified knowledge graph
• 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
• Collaborate with cross-functional stakeholders — data scientists, clinical documentation specialists, and R&D researchers — to translate domain requirements into scalable graph schemas and queries
• 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

Requirements:

• the role is not able to offer visa transfer or sponsorship now or in the future
• 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
• 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
• pandas, py2neo/neo4j-driver, FastAPI/Flask a plus