Quality Engineer-Data

Introduction A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. Your Role And Responsibilities As a Quality Engineer: Data, you will design and execute comprehensive data quality testing strategies for various data-intensive applications. You will develop a deep understanding of business requirements and design optimized test scenarios to ensure data quality and integrity. Your Primary Responsibilities Will Include Design Testing Strategies: Design and execute comprehensive data quality testing strategies for ETL, Big Data, and data-intensive applications, including BAO, MDM, and data migrations. Plan Testing Activities: Plan and execute testing activities, estimate work efforts, create test cases, and identify test environment and test data requirements. Execute Test Cases: Utilize manual and automation solutions to execute test cases, report test status, and perform defect creation, triage, and resolution. Analyze Test Outcomes: Analyze test outcomes for continuous improvements using analytical and cognitive techniques and tools. Develop Test Scenarios: Develop a deep understanding of business requirements and design optimized test scenarios to ensure data quality and integrity. Preferred Education Master's Degree Required Technical And Professional Expertise Data Quality Testing Exposure: Exposure to designing and executing comprehensive data quality testing strategies for ETL, Big Data, and data-intensive applications, including BAO, MDM, and data migrations. Test Planning and Execution Experience: Experience working with planning and executing testing activities, estimating work efforts, creating test cases, and identifying test environment and test data requirements. Manual and Automation Testing: Exposure to utilizing manual and automation solutions to execute test cases, report test status, and perform defect creation, triage, and resolution. Analytical Techniques Application: Experience applying analytical and cognitive techniques and tools to analyze test outcomes for continuous improvements. Business Requirements Understanding: Exposure to developing a deep understanding of business requirements and designing optimized test scenarios to ensure data quality and integrity. Preferred Technical And Professional Experience Data Migration Knowledge: Exposure to data migration processes and technologies, including data profiling and data validation techniques. Big Data Testing: Experience working with Big Data testing tools and methodologies, including Hadoop and Spark-based data processing. ETL Testing Tools: Exposure to ETL testing tools and frameworks, including Informatica PowerCenter and Talend.