Project Role : Data Management Practitioner

Project Role Description : Maintain the quality and compliance of an organizations data assets. Design and implement data strategies, ensuring data integrity and enforcing governance policies. Establish protocols to handle data, safeguard sensitive information, and optimize data usage within the organization. Design and advise on data quality rules and set up effective data compliance policies.

Must have skills : Graph Databases

Good to have skills : Neo4j, Python Frameworks

Minimum 5 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Summary:

As a Data Management Practitioner, a typical day involves overseeing the stewardship of an organization's data assets to ensure they meet quality and compliance standards. This role includes designing and implementing comprehensive data strategies that uphold data integrity and enforce governance policies. The practitioner establishes and maintains protocols for managing data securely, protecting sensitive information, and optimizing the use of data across various departments. Additionally, they provide guidance on data quality standards and develop effective compliance policies to support organizational objectives and regulatory requirements.

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.
Strong 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.