Goals:

• Drives and manages tasks to evaluate how well software meets quality expectations.
• Drives and articulates the development and implementation of team and group process improvements.
• Communicates the role of Software Testing and the value it adds to the business and may partner with organization peers to educate on specific Software Testing services.
• Mentors and guides the team to perform functional testing, nonfunctional testing, and other testing activities.

Major Responsibilities / Accountabilities:

• Applies technical expertise to clarify and understand requirements and ensures test approach and test coverage is defined for complex, largescale projects.
• Develops and maintains assigned testing deliverables as appropriate for the project methodology in place.
• Is able to execute multiple testing types such as integration, functional, regression testing, and performance tests as defined per project.
• Organizes and executes the plan for testing on various builds for complex, large-scale projects.
• Logs defects per defined project guidelines and standards and analyzes defects including the origin and cause, communicates pertinent information, and confirms resolution of defects.
• Directs the implementation of a technical solution that addresses a quality obstacle for a given product or system.
• May collaborate with other departments to determine the best and most efficient solution to complex technical challenges.
• Facilitates and/or leads reviews for user, functional, technical, and/or project requirements as appropriate for the project methodology in place to refine user stories, test plans, and test cases.
• Python, DBT, and SQL experience
• Participates in test automation code reviews.
• Drives technical discussions regarding the architecture of the system under test to enable the testing team to develop a comprehensive understanding and documentation.

Technical /Professional Skills & Competencies:

• Worked Data Quality Framework
• Write and execute test cases and test scripts to ensure the quality of data
• Write and define data quality metrics
• Worked on Data profiling, data cleansing, data reconciliation, data auditing, or data
• anomaly detection.
• Implement data validation and testing throughout the data engineering lifecycle
• Automating the data Quality process
• W orked on data testing tools like Informatica Data Validation, QuerySurge
• Datagaps ETL Validator, QualiDI or similar.