Data Engineer - ETL/PySpark (Banking Domain)

GSS Group • Python • SQL • ETL/ELT • 11 days ago
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Salary
≈ $17k – $65k per year (Estimated)
Location
In office (Bengaluru)
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GSS Group

GSS Group (Global Software Solutions Group) is an Emirati fintech software and enterprise solutions provider headquartered in Dubai Internet City. Specializing in the banking and financial services sectors, the company develops platforms for real-time payments, core banking, process automation, and document management across the Middle East, Africa, and India.
gsstechgroup.com • HQ: Dubai, United Arab Emirates • Software • Financial Services • FinTech • Est. 2021

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

Daily Tech Stack

  • Python
  • Spark / PySpark
  • Jupyter
  • SQL and NoSQL DBMS
  • Hadoop / MapReduce / Hive
  • Pandas
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