Data Engineer - ETL PySpark Banking Domain

About the role

We are seeking a hands‑on Data Engineer with deep expertise in ETL and PySpark to design, build, and maintain data pipelines and data marts for a banking environment. You will own the full software development lifecycle, from initial development through UAT, production deployment, and post‑production support.

Key responsibilities

• Design, develop, and maintain ETL pipelines and data marts using PySpark and Python.
• Write clean, production‑grade Python code following software‑engineering best practices.
• Own end‑to‑end SDLC activities: build, UAT support, bug fixing, deployment, and post‑production support.
• Perform data analysis and debugging with Oracle SQL and PySpark.
• Work with structured, semi‑structured, and unstructured data sources.
• Build and maintain data‑warehousing solutions for banking/financial reporting.
• Debug and optimise PySpark jobs for performance and reliability.
• Collaborate with QA, DBAs, and business analysts throughout the release cycle.
• Participate in CI/CD pipelines, including testing and validation of data pipelines.

Required profile

• 5+ years of commercial experience in a data‑engineering role.
• Hands‑on experience building data marts and ETL pipelines.
• Strong knowledge of banking or financial reporting requirements.
• Proven ability to manage the full SDLC for data pipelines.

Required skills

• Python
• PySpark / Spark
• Oracle SQL
• Hadoop, MapReduce, Hive
• Pandas
• CI/CD practices
• Jupyter notebooks
• Data‑warehousing fundamentals

What we offer

• Opportunity to work on critical banking data projects.
• Collaborative environment with cross‑functional teams.
• Exposure to modern big‑data technologies and best practices.