Quality Engineer-Data

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. 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. • Optimize Test Scenarios: Develop a deep understanding of business requirements and design optimized test scenarios to ensure data quality and integrity. • 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 to design optimized test scenarios ensuring data quality and integrity. • Data Migration Knowledge: Exposure to data migration processes and technologies is beneficial for designing comprehensive data quality testing strategies. • Big Data Testing: Experience working with Big Data testing tools and methodologies can be advantageous in executing data quality testing strategies. • BAO and MDM Understanding: Familiarity with Business Analytics Optimization (BAO) and Master Data Management (MDM) concepts can aid in designing optimized test scenarios. India Data & Analytics Hybrid Entry Level Multiple Cities

Responsibilities

Multiple Cities