ETL QA - Senior Engineer @ Iris Software

• 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: 6-8 years of hands-on experience in Data Quality Assurance, Data Testing, or ETL Testing roles.

SQL Expertise:

• Advanced proficiency in SQL: Ability to write complex queries, subqueries, analytical functions (Window functions), CTEs, and stored procedures for data validation, reconciliation, and analysis.
• Experience with various SQL databases (e.g., SQL Server, Oracle, PostgreSQL, MySQL, Snowflake, BigQuery).
• 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:

• 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).
• 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.