Roles & Responsibilities:
- Design and implement scalable ETL and ELT pipelines to ingest, transform, and load structured and unstructured data into graph databases.
- Build and maintain knowledge graph infrastructure on platforms such as Neo4j, Stardog, Amazon Neptune, Stardog, or Apache Jena including indexing, query optimization, and availability tuning.
- Write and optimize complex SPARQL, Cypher, and Gremlin queries for production graph workloads including traversal, inference, and aggregation.
- Implement SHACL or ShEx constraints and automated validation pipelines to enforce data conformance against ontology schemas.
- Develop APIs and microservices that expose graph data to downstream consumers — including search, recommendation, and LLM/RAG pipelines.
- Integrate knowledge graph layers with vector databases and embedding models to support hybrid semantic search and retrieval-augmented generation.
- Collaborate with ontology designers to implement and version ontology changes safely in production without disrupting dependent services.
- Monitor graph platform performance, diagnose bottlenecks, and drive reliability improvements across ingestion and query layers.
- Conduct code reviews, define engineering standards, and mentor mid-level and junior developers on graph engineering best practices.
- Contribute to documentation, runbooks, and internal tooling to support the broader knowledge graph team's productivity.

- Expected to be an SME,



collaborate and manage the team to perform.
- Responsible for team decisions.
- Engage with multiple teams and contribute on key decisions.
- Provide solutions to problems for their immediate team and across multiple teams.
- Lead initiatives to improve data governance frameworks and ensure alignment with organizational goals.
- Facilitate communication and coordination between cross-functional teams to promote data quality and compliance.
- Mentor junior team members to support their professional growth and enhance team capabilities.

Professional & Technical Skills:
- Must To Have Skills: Proficiency in Graph Databases, Neo4j, Python Frameworks.
- Good To Have Skills: Experience with Neo4j, Python Frameworks.
- Robust knowledge of data modeling and schema design specific to graph database technologies.
- Ability to develop and optimize queries for efficient data retrieval and manipulation within graph databases.
- Experience in implementing data governance policies and ensuring compliance with data protection regulations.
- Familiarity with integrating graph databases into broader data ecosystems and workflows.

Additional Information:
- The candidate should have minimum 5 years of experience in Graph Databases.
- This position is based at our Bhubaneswar office.
Education:
- A 15 years full time education is required.

📌 Graph Database Consultant (Bhubaneswar)
🏢 Cerebra
📍 Bhubaneswar