Graph Database Developer

Tekskills Inc.; Hyderabad; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Tekskills Inc. in Mumbai, MH, seeks a highly skilled Graph Database developer to design and implement graph-based data solutions in regulated environments such as pharma clinical development.

You will build scalable graph architectures, optimize queries, and deliver production-ready graph models and applications using Neo4j, Neptune, TigerGraph, or Cosmos DB Gremlin API, with Cypher, Gremlin, SPARQL, or GSQL.

Qualifications

• Hands-on experience designing graph data models for production systems.
• Proficient in Cypher, Gremlin, SPARQL, or GSQL.
• Experience with ingestion pipelines and data engineering concepts.
• Ability to operate in highly regulated environments.
• Experience in pharma or regulated industries is a plus.

Responsibilities

• Design, develop, and maintain graph data models and schemas using platforms such as Neo4j, Amazon Neptune, or Tiger Graph.
• Build and optimize graph query logic using Cypher, Gremlin, SPARQL, or GSQL.
• Develop ingestion and transformation pipelines to load structured and unstructured data into graph databases.
• Integrate graph databases with application services, APIs, and analytics pipelines.
• Collaborate closely with data science, data engineering, and platform teams to support AI driven relationship analytics.
• Contribute to system architecture and design to ensure scalability, high availability, and performance of graph‑based systems.
• Engage confidently with business stakeholders on graph related use cases, capabilities, and solution designs.

Skills

Graph DB

Cypher

Gremlin

SPARQL

GSQL

Data modeling

Data pipelines

Regulated env

Pharma exp

Collaboration

Tools

Neo4j

Cosmos DB Gremlin API

Neptune

TigerGraph

Job description

Job Title: Graph Database developer

Location: Mumbai, MH

Skills required: NoSQL Graph DB

Experience range: 8 to 10 years

Role Descriptions:

• We are seeking a highly skilled Graph Database developer to support the design and development of advanced graph-based data solutions in a regulated environment (e.g., pharma clinical development and RD).
• This role involves hands‑on engineering to build scalable graph architectures, optimize graph queries, and ensure production ready implementation of graph data models and graph‑powered applications.

Key Responsibilities:

• Design, develop, and maintain graph data models and schemas using platforms such as Neo4j, Amazon Neptune, or Tiger Graph.
• Build and optimize graph query logic using Cypher, Gremlin, SPARQL, or GSQL.
• Develop ingestion and transformation pipelines to load structured and unstructured data into graph databases.
• Integrate graph databases with application services, APIs, and analytics pipelines.
• Collaborate closely with data science, data engineering, and platform teams to support AI driven relationship analytics (e.g., knowledge graphs, entity resolution, graph ML).
• Contribute to system architecture and design to ensure scalability, high availability, and performance of graph‑based systems.
• Engage confidently with business stakeholders and cross functional teams on graph related use cases, capabilities, and solution designs.
  

Qualifications:

• Proven experience with major graph database technologies (Neo4j, Cosmos DB Gremlin API, Neptune, Tiger Graph, or equivalent).
• Strong proficiency in graph query languages such as Cypher, Gremlin, SPARQL, or GSQL.
• Understanding of graph theory, graph modeling, and relationship‑centric data design. Experience with data engineering concepts, pipelines, and ingestion frameworks.
• Excellent collaboration and communication skills.
• Ability to work in fast paced, highly regulated environments.
• Prior experience in pharma or other regulated industries is a plus.
• Experience building or supporting knowledge graphs is a significant advantage.
• Familiarity with integrating graph databases into AIML systems is a plus.
• Understanding of performance tuning, indexing strategies, and query optimization for graph workloads is a strong plus.