Senior PySpark Data Engineer - ETL & Data Warehousing

GSS Group

Dubai

On-site

AED 300,000 - 520,000

Full time

40 hours ago
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Job summary

GSS Group seeks a hands-on Data Engineer with strong ETL and PySpark expertise to design, build, and support data pipelines and data marts within a banking environment. The candidate will own the full SDLC lifecycle — from build through UAT, production deployment, and post-production support — while working across structured, semi-structured, and unstructured data.

Key responsibilities include designing ETL pipelines, maintaining production-grade Python code, and leading end-to-end deployment

Qualifications

  • 5+ years of commercial data engineering experience.
  • Hands-on experience building data marts and ETL pipelines.
  • Expert-level PySpark and Python for ETL scripting.
  • Strong command of Oracle SQL for data analysis and debugging.
  • Proven experience across the full SDLC — build, UAT, bug fixing, deployment, post-prod support.
  • Strong understanding of software engineering concepts and best practices for production pipelines.
  • Experience with structured, semi-structured, and unstructured data.
  • Prior banking client experience or strong banking domain knowledge.
  • Strong data warehousing fundamentals.

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, UAT bug fixes, production deployment, and post-production support.
  • Perform data analysis and debugging using Oracle SQL and PySpark.
  • Work across structured, semi-structured, and unstructured data sources.
  • Build and maintain data warehousing solutions supporting banking/financial reporting needs.
  • Debug and optimize PySpark jobs for performance and reliability.
  • Collaborate with cross-functional teams (QA, DBAs, business analysts) through the release cycle.
  • Participate in CI/CD pipeline processes, including testing and validation of data pipelines.
  • Ensure data pipeline reliability, scalability, and adherence to banking data governance/compliance standards.

Skills

ETL pipelines
PySpark
Python
SDLC
Banking domain knowledge

Tools

Spark/PySpark
Hadoop
MapReduce
Hive
Pandas
SQL/NoSQL DBMS
Jupyter
CI/CD
Airflow

Job description

GSS Group seeks a hands-on Data Engineer with strong ETL and PySpark expertise to design, build, and support data pipelines and data marts within a banking environment. The candidate will own the full SDLC lifecycle — from build through UAT, production deployment, and post-production support — while working across structured, semi-structured, and unstructured data.

Key responsibilities include designing ETL pipelines, maintaining production-grade Python code, and leading end-to-end deployment

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