The Role
Design and build a knowledge graph representing asset topology, ontologies, systems, and relationships. Populate the graph from integrated source data, provide query interfaces, and synchronize it with the lakehouse. Collaborate with architects and data engineers to support downstream insights, advanced analytics, and future agentic use cases. The role requires hands-on GraphDB expertise, semantic modeling, graph querying, and integration with broader data platforms.
Summary Generated by Built In
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.
- Strong 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.
- Strong self-learner who stays current with evolving tools, platforms, and practices.
- Good team player who collaborates well across engineering, operations, and stakeholder groups.
Skills Required
- 6+ years of experience in data engineering
- 3+ years of hands-on GraphDB or knowledge graph experience
- Hands-on experience with Neo4j, TigerGraph, or similar graph databases
- Ontology and semantic modeling experience
- Strong graph query skills using Cypher, Gremlin, SPARQL, or equivalent
- Ability to translate asset and topology data into a coherent graph model
- Experience integrating graph stores with broader data platforms
- Experience modeling industrial assets, facilities, or building topology
- Familiarity with RDF, OWL, and reasoning
- Exposure to graph-powered analytics or agentic use cases
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The Company
What We Do
Coditude stands out as a rapidly growing force in the digital realm, offering straightforward, impactful tech capabilities. Our team, both seasoned and savvy, is the perfect ally to thrive in the digital age. We excel in Product Development, SaaS Solutions, Enterprise Mobile Applications, AI, Cloud Solutions, Browser Extension Development, and Digital Commerce Solutions, not to mention our prowess in Infrastructure Modernization and Management
