NTT DATA is seeking a skilled Technology Consultant specializing in Database QA and ETL Testing. This role is crucial for ensuring the integrity and accuracy of data across our enterprise systems. You will collaborate with various teams to validate complex data pipelines and transformations, contributing to robust data solutions.

Join an inclusive, adaptable, and forward-thinking organization committed to accelerating client success and driving positive societal impact through innovation. We are a global leader in AI and digital infrastructure, offering unparalleled expertise in AI, cloud, security, and data services.

Perform comprehensive end-to-end database and ETL testing on source and target systems. Validate ETL/ELT pipelines, transformation logic, and business rules. Develop and execute complex SQL queries for data validation and defect analysis. Ensure source-to-target data accuracy, completeness, and consistency. Validate large-volume data loads, batch processes, and scheduled ETL jobs. Conduct database testing including tables, views, stored procedures, and functions. Validate data transformation rules, aggregations, and business logic. Perform data quality checks for completeness, uniqueness, accuracy, and integrity. Develop and execute test plans, cases, and regression suites. Identify data discrepancies, perform root cause analysis, and collaborate on defect resolution. Validate backend data for reports and downstream applications. Manage defects using Jira or similar tools and support SIT, regression, UAT, and production validation. Prepare detailed test execution and defect reports.

Requires a minimum of 5 years of experience in Database QA, ETL Testing, and Data Validation. Must have 5+ years of hands-on experience with SQL, complex query development, database testing, and data reconciliation. Possess 4+ years of experience testing ETL/ELT pipelines, source-to-target mappings, and data transformations. A minimum of 3 years of experience in data warehouse testing, data quality validation, and large-volume data processing is essential. Core technical skills include proficiency in SQL, Stored Procedures, Views, Functions, Data Validation, various databases (Oracle, SQL Server, PostgreSQL, MySQL), ETL tools (Informatica, DataStage, Talend, SSIS), Data Warehouse concepts, SIT, Regression, Integration, UAT Support, and defect management tools like Jira or Azure DevOps. Experience with Agile and Scrum methodologies is required.