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Strong Tier-1 brand, generic 'Data Analyst' title, and metro/mid-level demand increase competition.
Banking-specific ledger math, COBOL legacy familiarity, and domain knowledge limit transferability across industries.
Mandatory Oracle PL/SQL production experience and regulated banking context raise shortlisting rigor.
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Support and modernize a metadata-driven financial reporting data integration platform processing over 200M rows daily from 80+ source applications using Oracle PL/SQL.
Ensure production stability through rerun safety, parity validation, and ops handoff documentation.
Contribute to potential migration to AWS Databricks (PySpark/Python) by enabling dynamic SQL to Python translation and platform modernization.
Strong expertise in Oracle PL/SQL including dynamic SQL, partitioned tables, and performance tuning.
Experience in production discipline: rerun safety, parity validation, and documentation for operational handoff.
Problem-solving skills to validate data results and debug transformation issues effectively.
Work Experience Required: Not explicitly mentioned in the JD.
Familiar with banking domain concepts such as Average Daily Balancing math, General Ledger structures, and Month to Date accumulations.
Experienced with modern data engineering technologies including Databricks, PySpark, and AWS S3.
Comfortable with legacy system understanding, including COBOL literacy and translating COBOL-based processes to modern platforms.