Enterprise Solutions Graph Database/ Architect

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.