Data Engineer - Graph

IDFC FIRST Bank · Gurgaon

  • Experience2–6 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelmid
  • Posted2 Sept 2026
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About IDFC FIRST Bank

IDFC FIRST Bank is hiring in Gurgaon in financial services. This role looks for around 2+ years of experience.

Skills

  • graph data modeling
  • Neo4j
  • Amazon Neptune
  • TigerGraph
  • Dgraph
  • Cypher
  • Gremlin
  • Python
  • PySpark
  • Unix
  • Apache Airflow
  • ETL/ELT
  • Apache Kafka
  • data security
  • access control

The role

A data engineer at a banking organization designs graph databases for knowledge representation and real-time applications, using graph data modeling, Python, and PySpark to build scalable ingestion and analytics pipelines. The role develops graph query solutions and integrates diverse data sources through Apache Airflow and Apache Kafka.

Full job description

IDFC is seeking a highly motivated and experienced Data Engineer with a strong focus on graph databases to join the growing data team. In this role, you will be responsible for designing, building, and maintaining robust and scalable graph-based data solutions. You will work closely with data scientists, analysts, and application developers to leverage the power of graph databases for complex data analysis, knowledge representation, and real-time applications.

Responsibilities:

Design and implement efficient and scalable graph data models using appropriate graph database technologies (e. g., Neo4j, Amazon Neptune, TigerGraph, etc. ).

Translate business requirements into effective graph schemas and data structures.

Optimize graph models for performance and query efficiency.

Develop and maintain graph database instances, including installation, configuration, and performance tuning.

Implement data ingestion and transformation pipelines to populate graph databases from various data sources.

Develop and optimize Cypher, Gremlin, or other graph query languages for complex data retrieval and analysis.

Implement data security and access control mechanisms for graph databases.

Monitor and maintain the health of graph databases.

Design and implement ETL/ELT processes to integrate data from diverse sources into graph databases.

Develop and maintain data pipelines using tools like Apache Kafka, Apache Airflow, or similar technologies.

Ensure data quality and consistency throughout the data integration process.

Collaborate with data scientists and analysts to develop graph-based analytics solutions.

Develop and implement APIs and applications that leverage graph database capabilities.

Develop and implement algorithms for graph traversals, community detection, and other graph analytics tasks.

Secondary Responsibilities:

Identify and resolve performance bottlenecks in graph database systems.

Monitor and optimize query performance.

Troubleshoot and resolve data-related issues.

Document graph data models, data pipelines, and database configurations.

Establish and enforce best practices for graph database development and management.

Participate in code reviews.

Requirements:

2 to 6 years of experience in data engineering and proficiency in Python, PySpark, and Unix.

Experience with GraphDB, Amazon Neptune, TigreGraph, Dgraph, etc., and graph query languages like Cypher, Gremlin, etc.

Experience with Apache Airflow.

Excellent communication and problem-solving abilities.

Ability to work independently and manage tasks efficiently.

Bachelor's or master's degree in a relevant field (B. Sc., B. Tech., BCA, M. Sc., M. Tech., MCA).