# Graph Data Engineer

> Weekday AI · Mumbai, India · Full-time · Posted 2026-07-14

**Salary:** INR 1,000,000–5,000,000

**Workplace:** on_site

**Department:** Weekday's Client via platform

## Description

**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 efficient 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.

## Requirements

### 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.

### Required Skills

### Must-Have Skills

-   Strong proficiency in **Python** for data engineering, automation, scripting, and backend data processing.
-   Excellent knowledge of **SQL**, including complex joins, query optimization, stored procedures, and performance tuning.
-   Solid understanding of data modeling, ETL pipelines, and data integration techniques.
-   Experience working with relational databases and large-scale datasets.
-   Knowledge of distributed data processing concepts and scalable data architectures.
-   Strong analytical and problem-solving abilities with attention to data quality and performance.

### Good-to-Have Skills

-   Experience with graph databases such as **Amazon Neptune**, **TigerGraph**, or **Neo4j**.
-   Knowledge of graph query languages such as Cypher, Gremlin, or GSQL.
-   Familiarity with cloud platforms including AWS, Azure, or Google Cloud.
-   Exposure to data orchestration tools such as Apache Airflow or similar workflow management platforms.
-   Experience working with APIs, JSON, and semi-structured data.
-   Understanding of containerization technologies such as Docker and Kubernetes.

### Preferred Qualifications

-   Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field.
-   3–12 years of experience in data engineering, database development, or graph database implementations.
-   Experience designing scalable, high-performance data systems for enterprise applications.
-   Ability to work in Agile development environments and collaborate with cross-functional teams.
-   Excellent communication and documentation skills.

## Apply

[Apply at Weekday AI](https://apply.workable.com/weekday-1/j/90437388DC/apply)

---
Powered by [Workable](https://www.workable.com)
