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Strong Tier‑1 brand, popular product role, metro location and mid-level seniority increases competition.
Strong banking domain knowledge and COBOL legacy requirements reduce cross-industry transferability.
Requires specific PL/SQL/Databricks and banking domain skills, creating rigid technical filtering.
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Support and contribute to an existing data product team focused on delivering data products using PL/SQL and MSSQL, with a future shift to Databricks.
Own and improve data engineering processes including dynamic SQL, partitioned tables, performance tuning, and restartable processes.
Solve complex data transformation problems, validate data results, debug issues, and assist with technology selection for efficient data processing.
Strong expertise in Oracle PL/SQL and MSSQL including dynamic SQL and performance tuning.
Experience or familiarity with modern data engineering tools: Databricks, PySpark, AWS S3 (preferred, but not explicitly stated as mandatory).
Understanding of banking domain concepts such as Average Daily Balancing math, General Ledger structures, and legacy systems (desirable but not explicitly mandatory).
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in handling data engineering projects involving database optimization and dynamic SQL scripting.
Familiarity with banking domain data products and legacy banking systems, including COBOL-based systems.
Capable of supporting migration from traditional SQL-based systems to modern platforms like Databricks with skills in Python translation of SQL logic.