ETL QA - Lead

Key Responsibilities:
Data Testing Strategy & Execution: Design, develop, and execute comprehensive test plans and test cases for data-centric applications, ETL processes, data warehouses, data lakes, and reporting solutions. SQL-Driven Validation: Utilize advanced SQL queries to perform complex data validation, data reconciliation, data integrity checks, and data quality assurance across various financial data sources. ETL Testing: Conduct thorough testing of ETL (Extract, Transform, Load) processes, ensuring data is accurately extracted, transformed according to business rules, and loaded correctly into target systems. Data Quality Assurance: Implement and monitor data quality checks, identify data discrepancies, anomalies, and inconsistencies, and work with development and business teams to resolve issues. Performance Testing (Data Focus): Contribute to performance testing efforts for data pipelines and database operations, ensuring optimal query and data load performance. Test Data Management: Create and manage robust test data sets for various testing phases, including positive, negative, and edge case scenarios. Defect Management: Identify, document, track, and re-test defects in data, collaborating closely with development and data engineering teams for timely resolution. Documentation & Reporting: Maintain clear and concise documentation of test plans, test cases, test results, and data quality reports. Provide regular status updates to stakeholders. Collaboration: Work effectively with business analysts, data architects, data engineers, and project managers to understand data flows, business requirements, and ensure data quality standards are met. Process Improvement: Proactively identify opportunities for process improvements in data testing methodologies and tools. Global Team Collaboration: Provide consistent overlap with EST working hours (until noon EST) to facilitate effective communication and collaboration with US-based teams. Required Skills & Experience: Experience: 8-10 years of hands-on experience in Data Quality Assurance, Data Testing, or ETL Testing roles. SQL Expertise: o Advanced proficiency in SQL: Ability to write complex queries, subqueries, analytical functions (Window functions), CTEs, and stored procedures for data validation, reconciliation, and analysis. o Experience with various SQL databases (e. g. , SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, BigQuery). o Strong understanding of database concepts: normalization, indexing, primary/foreign keys, and data types. Data Testing Methodologies: Solid understanding of data warehousing concepts, ETL processes, and various data testing strategies (e. g. , source-to-target mapping validation, data transformation testing, data load testing, data completeness, data accuracy). Domain Expertise: o Strong understanding and proven experience in Risk and Finance IT domain: Familiarity with financial data (e. g. , trading data, market data, risk metrics, accounting data, regulatory reporting). o Knowledge of financial products, regulations, and risk management concepts. Analytical & Problem-Solving Skills: Excellent ability to analyze complex data sets, identify root causes of data issues, and propose effective solutions. Communication: Strong verbal and written communication skills to articulate data issues and collaborate with diverse teams.

Mandatory Competencies