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Mid-level and metro location, moderate brand with niche graph specialization reduces applicant density.
Graph engineering skills transfer across industries but BFSI-focused ontology work raises domain sensitivity.
Mandatory 5+ years plus specific Neo4j, Cypher, Python and graph modeling skills imply medium strictness.
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Design and implement BFSI domain-specific ontology models and graph schemas for engineering use cases.
Develop and optimize entity and relationship extraction pipelines, graph ingestion, transformation, and traversal/query logic.
Collaborate with AI engineers to support GraphRAG implementation and improve graph performance and semantic accuracy.
Minimum 5+ years of experience in designing and implementing ontology models, entity relationships, graph structures, and semantic enrichment pipelines.
Proficiency in Neo4j and Cypher, Python data engineering, SQL, and graph data modeling.
Experience with metadata and lineage concepts, entity relationship modeling, and data transformation.
BFSI domain knowledge or exposure is preferred but not explicitly mandatory.
Strong expertise in graph database technologies and semantic web concepts relevant to BFSI use cases.
Experienced in implementing scalable graph ingestion and traversal strategies with measurable performance improvements.
Able to work closely with AI teams to integrate graph data with retrieval-based AI models.