Enterprise Solutions Graph Database/ Architectwith AnzoGraph

Enterprise Solutions Graph Database/ Architectwith AnzoGraph

Posted 1 day ago by Headway Tek Inc

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Negotiable
Undetermined
Remote
Remote
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Algorithms Cloud Computing Cloud Migration Cloud Technology Data Science Graph Database Gremlin Java (Programming Language) Knowledge Graph Machine Learning Neo4j Ontologies Python (Programming Language) Query Performance Scalability SPARQL Protocol And RDF Query Language (SPARQL) Stakeholder Management Strategic Roadmaps

Job title : Enterprise Solutions Graph Database/ Architect with AnzoGraph (MUST HAVE)

Location : Upper Providence Township, PA (Remote)

Experience : 15 Years

Type :C2C or W2 or Fulltime

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).

Key Responsibilities

  • Platform Assessment: Conduct a "health check" on current graph infrastructure (e.g., AnzoGraph, Neo4j, or Stardog).
  • Ontology & Schema Review: Evaluate existing schemas (RDF/OWL or Property Graph) for scalability and alignment with industry standards like MeSH, SNOMED, or UMLS.
  • Performance Optimization: Identify bottlenecks in ingestion pipelines and complex query execution (Cypher/SPARQL).
  • Strategic Roadmap: Define a "Way Forward" report including recommendations on build-vs-buy decisions, cloud migration, and integration with LLMs (GraphRAG).
  • Stakeholder Alignment: Translate technical graph concepts into value-driven insights for non-technical stakeholders in Research and Clinical teams.

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 (MUST HAVE), Neo4j, Stardog,
  • Languages: Python, Java, SPARQL, Cypher, or Gremlin.
  • Bio-Ontologies: Familiarity with OBO Foundry, ChEMBL, or Ensembl.

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