Sr. Software QA Engineer
Posted Updated 1
view
Summary
A Sr. Data QA Engineer ensures data pipelines, workflows, and transformations in Databricks are accurate and reliable by designing test cases, validating data quality, and managing defect tracking with Xray/Jira. Core focus: SQL, Python, and ETL validation in Moody’s data-driven environments.
Skills and Competencies
- 4+ years of experience in Software Quality Assurance or Data Engineering roles supporting data or application platforms
- Strong experience with Databricks for validating data pipelines, workflows, and transformations
- Hands-on experience with Xray and Jira for test management, traceability, and defect tracking preferred
- Experience executing functional, integration, regression, and data validation testing across complex systems
- Advanced SQL skills for data analysis, validation, and troubleshooting data quality issues
- Experience working with ETL processes, data pipelines, or data warehouse environments.
- Strong Python skills for automation, scripting, or test data validation activities
- Basic understanding of artificial intelligence concepts, with curiosity and enthusiasm for learning how AI tools can be used to improve processes and drive efficiency. Interest in exploring AI systems and a willingness to develop awareness of responsible AI practices, including risk management and ethical use.
Education
- Bachelor’s degree in Computer Science, Information Technology, Software Engineering, Information Systems, or related field
- Equivalent combination of education and relevant experience may be considered
Responsibilities
- Support quality assurance activities for data platforms, applications, and reporting solutions to ensure accuracy, reliability, and performance
- Design and Execute test cases and document results for software releases across multiple environments
- Perform functional, integration, regression, and data validation testing for data-driven applications
- Validate data quality across Databricks workflows, ETL pipelines, and reporting outputs
- Manage test execution, traceability, and defect tracking using Xray and Jira
- Analyze defects and perform root cause investigation in collaboration with development teams
- Participate in requirements reviews and agile ceremonies to ensure quality standards are met
- Support user acceptance testing and release validation activities
- Contribute to continuous improvement of testing frameworks, processes, and quality practices
About the Team
Our Data Estate team delivers scalable and reliable data solutions that support business decision-making across Moody’s. The team partners closely with technology and business stakeholders to improve data quality, enhance operational efficiency, and drive innovation through the adoption of emerging technologies, including artificial intelligence.