Associate Director - Data Platform Product Manager
About the role
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. The Data Platform Product Manager owns a data engineering squad responsible for building and operating one of Moody’s Analytics’ core data platforms. Our data platform team has a strong bias toward rapid, reliable delivery of new data sets, while maintaining high standards for data quality, controls, and governance. This position is part of the Data Product Management Team, a dynamic, analytical group that is curious about data but relentlessly focused on driving value for customers and the business. Key
Responsibilities Own a data engineering squad, accountable for roadmap planning, execution, and delivery Drive effective delivery by accelerating decision making, removing blockers, and keeping
the team focused on the highest value outcomes for customers and the business Partner with the Data Platform Product Owner, Data Governance, Quality Assurance, Data Engineering, and internal Product Development teams to bring new data sets to market Collaborate closely with data engineers to understand solution complexity, evaluate architectural tradeoffs, and select implementation approaches that balance speed, scalability, cost, and AI readiness Manage agile ceremonies and execution (sprint planning, backlog refinement, reviews, retrospectives) to ensure consistent, high quality delivery Facilitate alignment across data and product development squads to manage dependencies and enable sound decision-making Own and prioritize a backlog consisting of user stories, defects, refactors, infrastructure work, and production support, prioritized by business value, platform reuse, risk reduction, and AI enablement Use AI and GenAI tools as part of day to day product management, including: Accelerating creation, refinement, and validation of product