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# Enterprise Solutions Graph Database

- **Company:** H R PUNDITS INC
- **Location:** Upper Providence Township, PA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Query Performance, Java (Programming Language), Information Engineering, Extract Transform Load (ETL), Graph Database, Python (Programming Language), Laboratory Information Management Systems, Linked Data, Machine Learning, Neo4j, Semantic Web, SPARQL, Systems Integration, Data Pipelines
- **Published:** August 9, 2026
- **Apply:** https://www.wayup.com/i-j-Enterprise-Solutions-Graph-Database-H-R-PUNDITS-INC-676357538636240/

## About the Role

Required Qualifications Graph Expertise: 10+ years of experience with Graph Databases. Deep proficiency in LPG (Labeled Property Graphs) or RDF/Triple Stores. Pharma Domain Knowledge: Proven experience handling biomedical data types (e.g., Gene-Disease associations, Chemical compounds, Patient journeys). Semantic Web Standards: Strong understanding of Linked Data principles, URI strategies, and ontology modeling. Data Engineering: Experience with ETL/ELT pipelines that feed graphs from unstructured (PDF publications) and structured (EDC, LIMS) sources. Advanced Analytics: Experience implementing Graph Data Science algorithms (centrality, community detection) or integrating Graphs with Machine Learning. Technical Stack Preferences Graph DBs: AnzoGraph, Neo4j, Stardog, Languages: Python, Java, SPARQL, Cypher, or Gremlin. Bio-Ontologies: Familiarity with OBO Foundry, ChEMBL, or Ensembl.

## Description

Job title : Enterprise Solutions Graph Database/ Architect Location: Upper Providence Township, PA (Onsite/Remote ) Experience : 15 Years
Role Overview Seeking a seasoned Graph Database Knowledge Graph Expert to perform a comprehensive study of our existing platform. Evaluate our current architecture, data ontology, and query performance to provide a strategic roadmap. The goal is to evolve our Knowledge Graph into a robust, scalable engine that accelerates different Pharma areas ( drug discovery, clinical insights, and cross-departmental data democratization)


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