Role Proficiency:

Ensuring adherence to test practices and process to improve test coverage

Outcomes:

     Create Test Estimates and Schedules      Identify business processes conduct risk analysis and ensure test coverage      Ensure adherence of processes and standards      Produce test results defect reports test logs and reports for evidence of testing      Publish RCA reports and preventive measures      Report progress of testing      Contribute for Revenue savings for client by suggesting alternate method Quality of Deliverables

Measures of Outcomes:

Test Script Creation and Execution Productivity Defect Leakage Metrics (% of defect leaked % of UAT defects and % of Production defects) % of Test case reuse Test execution Coverage Defect Acceptance Ratio Test Review efficiency

Outputs Expected:

Test Design
Development
Execution:

Participate in review
walkthrough
demo and obtain sign off by stakeholder for Test Design Prepare Test summary report for modules/features

Requirements Management:

Analyse
Prioritize
Identify Gaps and create workflow diagrams based on Requirements/User stories

Manage Project:

Participate in Test management

Domain relevance:

Identify business processes
conduct risk analysis and ensure test coverage

Estimate:

Prepare Estimate
Schedule
Identify dependencies

Knowledge Management:

Consume
Contribute
Review (Best Practices
Lesson learned
Retrospective)

Test Design
Execution:

Test Plan preparation
Test Case/Script Creation
Test Execution

Test & Defect Management:

Conduct root cause and trend analysis of the defects

Test Planning:

Identify the test scenarios with understanding of systems
interfaces and application Identify end-to-end business critical scenarios with minimal support Create/Review the test scenarios and prepare RTM

Skill Examples:

     Ability to create and manage a test plan      Ability to prepare schedules based on estimates      Ability to track and report progress      Ability to identify test scenarios and prepare RTM      Ability to analyse requirement/user stories and prioritize testing      Ability to carry out RCA Ability to capture and report metrics

Knowledge Examples:

     Knowledge of Estimation techniques      Knowledge of Testing standards      Knowledge of identifying the scope of testing      Knowledge of RCA Techniques      Knowledge of Test design techniques Knowledge of Test methodologies

Additional Comments:

Job Title: ETL QA Engineer (DataStage / IBM Netezza) Job Summary: We are seeking an experienced ETL QA Engineer to ensure the quality and reliability of our data pipelines and integration solutions. The ideal candidate will have a strong background in ETL testing with proficiency in IBM DataStage and IBM Netezza. This role involves collaborating with developers, business analysts, and other stakeholders to validate data transformations and ensure data accuracy, consistency, and completeness throughout the ETL process. Key Responsibilities: Design, develop, and execute test cases and test plans for ETL processes involving IBM DataStage and IBM Netezza to ensure data quality and integrity. Validate ETL workflows, data transformations, and end-to-end data flows. Perform data validation and reconciliation for data migration projects and ensure data accuracy between source and target systems. Conduct regression, functional, integration, and performance testing on ETL processes. Work with cross-functional teams to gather requirements, clarify business rules, and define test criteria. Analyze test results, report defects, and work with developers to ensure timely resolution. Create and maintain documentation for test strategies, test cases, and test execution results. Use SQL for data extraction, validation, and verification on various data sources, especially IBM Netezza. Automate repetitive testing processes and data validation tasks when applicable. Qualifications: Education: Bachelor’s degree in Computer Science, Information Systems, or a related field. Experience: 3+ years of experience in ETL and data warehousing testing with hands-on expertise in IBM DataStage and IBM Netezza. Proficient in writing complex SQL queries to validate data accuracy and integrity. Strong understanding of data warehousing concepts, ETL workflows, and data quality assurance principles. Experience with automation frameworks and tools is a plus. QA Automation in Data engineering side. Familiarity with Agile/Scrum methodologies. Strong analytical and problem-solving skills. Excellent communication and collaboration skills. Preferred Skills: Experience with other ETL tools or databases (e.g., Informatica, Talend). Knowledge of cloud-based data warehousing solutions. Familiarity with scripting languages (Python, Shell scripting).