Data Engineer - ETL/PySpark (Banking Domain)

On-siteSeniorData Engineerposted 5d ago

✦Role summaryAI-generated

Design and maintain PySpark‑based ETL pipelines and data marts for a banking environment, handling the full SDLC from development through production support. Requires 5+ years of experience with Python, Oracle, CI/CD, and data engineering best practices.

Skills required

Spark Python ETL Oracle CI/CD Data warehousing Data testing Software engineering SQL Data analysis NoSQL Data pipelines Hadoop pandas

About this role

Role Summary

We are looking for a hands-on Data Engineer with strong PySpark and Python expertise to build and maintain data marts and ETL pipelines within a banking environment. The ideal candidate owns the full SDLC, from build through UAT, bug fixing, production deployment, and postproduction support.

Key Responsibilities

Design, build, and maintain ETL pipelines and data marts using PySpark and Python
Write clean, maintainable, and robust production-grade code
Own end to end SDLC activities: build, UAT, UAT bug fixes, production deployment, and postproduction support
Perform Oracle query analysis and PySpark code debugging
Work across structured, semi structured, and unstructured data sources
Apply software engineering best practices to production pipelines
Support CI/CD processes and data testing/validation activities

Required Skills & Experience

5+ years commercial experience in a data-driven role
Hands-on experience building data marts and ETL pipelines
Expert level Python for ETL scripting
Strong PySpark experience
Analytical expertise in Oracle SQL and data analysis
Understanding of software engineering concepts and best practices for production pipelines
Banking client or banking domain knowledge
Strong Data Warehousing fundamentals
Familiarity with query languages and both SQL and NoSQL database technologies
CI/CD exposure, including testing and validation of data pipelines