What You Bring (required qualification and skill sets)
· Bachelor’s/Master’s in CS, Data Science, Mathematics, Engineering, or related field.
· 7–12 years in graph databases, semantic modeling, ontology engineering.
· Deep expertise in Cypher, Gremlin, SPARQL; strong command of LPG vs RDF/OWL tradeoffs.
· Hands-on with Neo4j, AWS Neptune, TigerGraph, Stardog (at least one in production).
· Experience mapping enterprise data (Snowflake/MongoDB/SharePoint/ERP) into graph/ontology layers.· Strong understanding of RBAC/RACI, data governance, lineage, and security controls.
· Strong understanding of RBAC/RACI, data governance, lineage, and security controls.
· Ability to design clean APIs and reference implementations for semantic enrichment/retrieval.
· Practical AWS familiarity (IAM, VPC, S3, EKS/ECS/Lambda) in collaboration with platform teams.
Preferred Qualifications
· Ontology tooling (Protégé, SHACL/SWRL), reasoning engines, and constraint modeling.
· Prior delivery of enterprise knowledge graphs supporting workflows & audit trails.
· Exposure to vector retrieval/RAG and how graph context informs re-ranking.
· Observability awareness (tracing across graph layers, OpenTelemetry, Prometheus/Grafana).
· Experience with Snowflake/MongoDB/SharePoint APIs and ERP data structures.
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