> Markdown version of [/jobs/ext/3799442-graph-engineer-chicago-il-onsite](https://www.wearedevelopers.com/jobs/ext/3799442-graph-engineer-chicago-il-onsite). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Graph Engineer - Chicago, IL - Onsite - **Company:** Gandiva Insights - **Location:** Chicago, IL, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Microsoft Azure, Bioinformatics, Cloud Computing, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Graph Database, Python (Programming Language), Neo4j, Named Entity Recognition, Performance Tuning, SPARQL, Unstructured Data, Data Processing, Fast Healthcare Interoperability Resources, Git, Information Technology, Api Design - **Published:** October 17, 2026 - **Apply:** https://www.careerjet.com/jobad/us9b2a8c89b4f8ffa5ac22782a6ab2d716 ## About the Role 3 4 years of experience with Neo4j or other graph databases. Strong Python skills for ETL pipelines, data processing, and API development. Experience with Cypher queries, graph schema design, and performance tuning. Working knowledge of AWS, Azure, or GCP. Understanding of data modeling, Git, and CI/CD basics. Bachelor's degree in Computer Science, Data Engineering, Bioinformatics, or a related field. Preferred Skills: Pharma or life sciences domain experience. Knowledge of FHIR, CDISC, UMLS, or MeSH. Experience with NLP, entity extraction, RDF, or SPARQL. ## Description We are looking for a Graph Engineer with hands-on experience in Neo4j, Python, and cloud technologies to build and maintain knowledge graphs supporting pharmaceutical research and clinical documentation., Design and develop graph data models using Neo4j. Build Python-based ETL pipelines to integrate structured and unstructured data. Develop and optimize Cypher queries and APIs. Deploy and maintain graph databases on cloud platforms. Ensure data quality, security, and compliance with pharma industry standards. Collaborate with data scientists and R&D teams to support knowledge discovery.