Job Summary
Develop and support scalable data solutions for a banking client using Python, PySpark, SQL and Oracle. The candidate should have strong hands-on data pipeline, transformation and large-volume processing experience.
Key Responsibilities
• Design and maintain data pipelines using Python and PySpark.
• Build ETL/ELT processes for extraction, transformation, validation and loading.
• Work extensively with Oracle and SQL for data processing and reconciliation.
• Develop data models and transformations for large datasets.
• Optimize PySpark jobs, SQL queries, joins and partitioning.
• Implement data-quality checks, error handling and production support.
• Collaborate with application, database, QA and DevOps teams.
Required Skills
• Strong Python and PySpark experience.
• Strong SQL and Oracle database experience.
• Experience with ETL/ELT, data pipelines and data modeling.
• Knowledge of Spark DataFrames, joins, transformations, partitioning, caching and optimization.
• Experience troubleshooting production data issues.
• Banking/financial-services experience preferred.
Good to Have
• Databricks
• AWS/Azure
• Kafka
• Airflow
• Snowflake/Data Lake
• GenAI/ML
Key Skills: Python, PySpark, Data Modeling, SQL, Oracle

Python Data Engineer

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