Phase: Initial phase for design, expanding in later phases

Required experience: 6+ years in data engineering, with 3+ years hands-on GraphDB / knowledge graph work.

Role summary

Designs and builds the graph layer that models asset topology and ontology. Turns the connected structure of assets, systems, and relationships into a queryable knowledge graph that complements the lakehouse and enables richer downstream use cases.

Key responsibilities
Design the graph data model for asset topology and ontology.
Build and populate the knowledge graph from integrated source data.
Define ontologies and relationships that reflect the physical and operational asset estate.
Provide graph query interfaces for insights and downstream applications.
Collaborate with the architect and data engineers to keep the graph in sync with the lakehouse.
Prepare the graph layer to support agentic and advanced analytics use cases in later phases.

Must-have skills and experience
Hands-on GraphDB / knowledge graph experience (Neo4j, TigerGraph, or similar).
Ontology and semantic modeling experience.
Solid graph query skills (Cypher, Gremlin, SPARQL, or equivalent).
Ability to translate asset and topology data into a coherent graph model.




Comfort integrating graph stores with a broader data platform.

Nice to have
Experience modeling industrial assets, facilities, or building topology.
Familiarity with RDF / OWL and reasoning.
Exposure to graph-powered analytics or agentic use cases.

Relevant stack

GraphDB (Neo4j / TigerGraph or similar), Cypher / Gremlin / SPARQL, RDF / OWL, integrated with Azure / Snowflake data platform.

General attributes
Proactive and self-driven, able to take ownership and move work forward without waiting to be told.
AI-enabled in day-to-day work, comfortable using AI tools and copilots to accelerate delivery and quality.
Solid self-learner who stays current with evolving tools, platforms, and practices.
Positive team player who collaborates well across engineering, operations, and stakeholder groups.

Required Skills

Graph query languages Neo4j, TigerGraph, or similar Ontology and semantic modeling Cypher, Gremlin, or SPARQL

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Graphdb / Knowledge Graph Engineer Pune
🏢 Codiste
📍 Pune