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
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Design, build, and maintain ETL pipelines and data marts using PySpark and Python
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Write clean, maintainable, and robust production-grade code
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Own end to end SDLC activities: build, UAT, UAT bug fixes, production deployment, and postproduction support
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Perform Oracle query analysis and PySpark code debugging
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Work across structured, semi structured, and unstructured data sources
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Apply software engineering best practices to production pipelines
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Support CI/CD processes and data testing/validation activities
Required Skills & Experience
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5+ years commercial experience in a data-driven role
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Hands-on experience building data marts and ETL pipelines
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Expert level Python for ETL scripting
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Strong PySpark experience
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Analytical expertise in Oracle SQL and data analysis
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Understanding of software engineering concepts and best practices for production pipelines
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Banking client or banking domain knowledge
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Strong Data Warehousing fundamentals
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Familiarity with query languages and both SQL and NoSQL database technologies
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CI/CD exposure, including testing and validation of data pipelines
Daily Tech Stack
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Python
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Spark / PySpark
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Jupyter
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SQL and NoSQL DBMS
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Hadoop / MapReduce / Hive
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Pandas
