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At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.
If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.
10+ years of experience in Software Quality Assurance or Data Quality Engineering, including automation-first testing for complex enterprise data platforms
Strong hands-on experience with Databricks SQL and Python, including testing of notebooks, workflows, pipelines, and scheduled jobs
Solid understanding of Medallion architecture (Bronze, Silver, Gold) and data lifecycle validation practices across enterprise data ecosystems
Expertise in PySpark for data validation, test automation, and building scalable, reusable testing frameworks
Strong proficiency in SQL and data validation techniques across dataset, record, schema, transformation, and source-to-target mapping levels
Experience working in Agile or Scrum environments with tools such as Xray for test management and Jira for defect tracking
Proven experience leading quality assurance initiatives, mentoring team members, driving quality governance, managing stakeholder expectations, and influencing delivery decisions
Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use.
Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field
Ensure data quality, reliability, and correctness across large-scale data platform pipelines through automated validation and testing practices
Lead end-to-end data quality validation across Bronze, Silver, and Gold data layers, establishing testing standards and quality gates across projects
Define and drive the overall quality assurance strategy, test approach, automation roadmap, and release readiness criteria for enterprise data platform initiatives
Mentor and provide technical leadership to quality assurance engineers by reviewing test plans, automation frameworks, validation logic, defect analysis, and quality metrics
Collaborate with engineering, platform, product, and architecture teams to influence solution design, identify quality risks early, and ensure testability of data solutions
Own quality governance activities including test execution reviews, defect triage, risk assessments, root cause analysis, and executive-level status reporting
Drive continuous improvement initiatives by identifying opportunities to enhance automation coverage, testing efficiency, data quality controls, and operational excellence
Act as the primary quality assurance point of contact for stakeholders, providing leadership during releases, production validation, issue resolution, and audit or compliance reviews
Our Data Platform and Engineering team is responsible for building and maintaining scalable, high quality data solutions that power critical business insights and analytics. By joining this team, you will collaborate with cross-functional experts across engineering, product, and platform functions to drive innovation in modern data architectures using Databricks and Delta Lake. The team is committed to adopting automation, advanced analytics, and responsible AI practices to ensure reliable and high performing data ecosystems.
Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.
Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.
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