Key Responsibilities

• Requirement Dissection: Thoroughly analyze business and technical requirements to ensure data pipelines meet complex banking compliance and logic standards.

• End-to-End ETL Validation: Design and execute testing strategies for large-scale data movements within Azure Data Factory (ADF).

• Complex SQL Engineering: Write and optimize advanced SQL queries (CTEs, Window Functions, Analytical Joins) to validate data transformations and warehouse performance.

• Data Modeling Oversight: Analyze and map conceptual, logical, and physical data models, ensuring star/snowflake schemas are optimized for financial reporting.

• Banking Domain Excellence: Apply deep knowledge of CIF, KYC, and AML processes to ensure data reflects the true transaction lifecycle and regulatory requirements (Basel, CCAR).

Required Skills & Experience

Technical Core

• 5+ Years Experience: Proven track record in database and ETL testing, specifically within financial or banking environments.

• SQL Mastery: Expert-level SQL skills, including complex joins, windowing functions, and analytical performance tuning.

• Cloud Data Warehousing: Hands-on experience with Snowflake (schema design, warehouse performance, stages, and ingestion) and Azure Data Factory.

• Data Modeling: Strong understanding of dimensional modeling, fact/dimension structures, and mapping transformations to warehouse architectures.

• Domain Knowledge (Banking/Finance)

• Solid grasp of Transaction Lifecycle data and GL/ledger balancing.

• Familiarity with risk and regulatory data models (CCAR, Basel).

• Experience handling sensitive KYC/AML and Customer Information File (CIF) datasets.

Process & Soft Skills

• Analytical Rigor: A proven ability to identify edge cases in complex financial requirements.

• Agile Proficiency: Comfortable working in fast-paced Agile environments with integrated QA processes.

• Communication: Ability to translate technical data discrepancies into business-level risks.