This role is for one of the Weekday's clients
Salary range: Rs 1000000 - Rs 5000000 (ie INR 10-50 LPA)
Min Experience: 3+ years
Location: Mumbai,Bangalore
JobType: full-time
We are seeking a highly skilled Graph Data Engineer to design, build, and optimize graph-based data solutions that power complex relationships, connected datasets, and advanced analytics. You will play a key role in developing scalable data pipelines, graph models, and query frameworks that enable effective exploration of interconnected data across large-scale systems.
The ideal candidate has strong expertise in Python and SQL, along with hands-on experience in data engineering, ETL development, and database optimization. Exposure to graph database technologies such as Amazon Neptune, TigerGraph, or Neo4j is highly desirable. This role offers the opportunity to work on cutting-edge data architectures and solve challenging problems involving highly connected data.
Key Responsibilities
Design, develop, and maintain scalable graph data pipelines and data integration workflows.




Build and optimize graph data models to represent complex business relationships efficiently.
Develop robust data ingestion, transformation, and validation processes using Python.
Write optimized SQL queries for data extraction, transformation, reporting, and analytics.
Design efficient graph traversals and queries to support business applications and analytical workloads.
Collaborate with software engineers, data scientists, and product teams to understand data requirements and translate them into scalable graph solutions.
Monitor data quality, consistency, and integrity across multiple data sources.
Optimize database performance, indexing strategies, and query execution for high-volume datasets.
Develop reusable data engineering frameworks and automation scripts.
Troubleshoot production issues and continuously improve system performance and reliability.
Document graph schemas, data pipelines, and engineering best practices.

📌 Graph Data Engineer (Mumbai)
🏢 Weekday AI
📍 Mumbai