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Data Engineer - ETL PySpark Banking Domain

Talentmate

United Arab Emirates

23rd August 2026 2608-8251-62

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Job Description

Role Summary

We are looking for 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 ideal 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

Design, develop, and maintain ETL pipelines and data marts using PySpark and Python
Write clean, maintainable, and 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

Required Skills & Experience

5+ years of commercial experience in a data-driven engineering role
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 working with structured, semi-structured, and unstructured data
Prior experience with banking clients or strong banking domain knowledge
Strong data warehousing fundamentals

Tech Stack (Daily Use)

Languages: Python
Big Data: Spark / PySpark, Hadoop, MapReduce, Hive
Data Libraries: Pandas
Databases: SQL and NoSQL DBMS
Tools: Jupyter
Practices: CI/CD, data testing & validation

Nice to Have (optional — add if applicable)

Cloud experience (AWS/Azure/GCP) — not mentioned in your input, confirm with client
Airflow or other orchestration tools
Experience with regulatory/compliance reporting in banking

Job Details

Role Level:	Mid-Level	Work Type:	Full-Time
Country:	United Arab Emirates	City:	Dubai
Company Website:	https://www.gsstechgroup.com/	Job Function:	Data Science & AI
Company Industry/ Sector:	IT Services and IT Consulting

What We Offer

About the Company

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