Data Engineer - ETL/PySpark (Banking Domain)

Global Software Solutions Group
Dubai, Dubai, United Arab Emirates
Salary not specified
Posted
Full-time
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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

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Dubai, United Arab Emirates
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