Data Engineer (Python/PySpark)

Job Summary […] is seeking a Data Engineer with 5+ years of experience building data marts, ETL pipelines, and large-scale data processing solutions.

will develop reliable data products using Python, PySpark, SQL, and data warehousing technologies while supporting the full software development lifecycle. Software

Required Python: 5+ years of development experience. PySpark/Spark: 3+ years of experience. Oracle SQL: 3+ years, including query optimization and data analysis.

Pandas and Jupyter Notebook. ETL development and data warehousing. Hadoop, Hive, and MapReduce.

SQL and NoSQL databases. Git, CI/CD tools, automated testing, and data validation. Experience supporting development, UAT, production deployment, and production issues.

Preferred Cloud-based data platforms. Workflow orchestration tools. Data quality and monitoring tools.

Banking or financial services data experience. Overall

Design, develop, and maintain scalable ETL pipelines using Python and PySpark. Build and optimize data marts and transformation processes. Process structured, semi-structured, and unstructured data.

Analyze and resolve data issues using Oracle SQL, PySpark, and data analysis techniques. Support development, testing, UAT, deployment, and production operations. Collaborate with engineering, QA, business, and operations teams.

Apply coding standards, testing practices, and CI/CD processes. Improve data quality, pipeline performance, reliability, and ma