Let's begin! Data Product Manager (13436)

About the Team

The Data Estate Data Platform team is part of the broader Data Product Management organization at Moody's Analytics. The team is a dynamic, analytical group with a strong bias toward rapid and reliable delivery of high-quality data assets. We partner closely with data engineering, governance, and product development teams to bring trusted, well-governed data to market, enabling analytics- and AI-driven products that create meaningful value for customers and the business.

Responsibilities

Owns and leads a data engineering squad responsible for building and operating one of Moody's Analytics' core data platforms, with a strong focus on delivering high-quality, governed data that drives customer and business value.

• 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
• 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 including sprint planning, backlog refinement, reviews, and retrospectives to ensure consistent, high-quality delivery
• Facilitate alignment across data and product development squads to manage dependencies and support sound decision making
• Own and prioritize a backlog of user stories, defects, refactors, infrastructure work, and production support based on business value, platform reuse, risk reduction, and AI enablement
• Use AI and GenAI tools to accelerate requirements creation, summarize stakeholder input and operational insights, and support impact analysis and root cause exploration
• Identify opportunities to automate and augment data delivery workflows, including data quality validation, documentation, metadata management, and operational reporting
• Coordinate release readiness and deployments with Release Management, Operations, Data Quality, and Data Governance partners
• Build strong relationships with data strategy and business stakeholders to support delivery of new data sets and evolution of existing data assets
• Embed data quality, lineage, and governance standards into backlog items and acceptance criteria, with particular focus on data used by AI- and model-driven products
• Proactively identify and mitigate delivery, quality, privacy, and operational risks across the data lifecycle

Skills and Competencies

• Strong grasp of agile methodologies and delivery practices
• Experience in technical product management or data engineering for data-intensive B2B products
• Prior experience in data platform, data warehousing, or analytics environments such as Snowflake, Databricks, Redshift, Athena, or Kafka
• Experience defining, monitoring, and operationalizing data quality and QA standards, particularly for downstream analytics or AI consumers
• Proficiency with SQL for data analysis, troubleshooting, and validation
• Familiarity with how data is consumed by machine learning or AI systems
• Results-oriented and action-focused mindset with the ability to drive delivery in complex, matrixed environments
• Strong communication skills with the ability to translate complex data and platform concepts for technical and non-technical stakeholders
• Strong analytical skills, persistence in problem solving, and attention to detail
• Demonstrated initiative, curiosity, and commitment to continuous improvement
• Experience working with vendors or external partners in a matrixed organization
• Track record of improving team and organizational effectiveness through influence and scalable processes
• 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

Education

• Bachelor's degree required; advanced degree such as an MBA or Master's preferred

Compensation and Benefits

For US-based roles only: the anticipated hiring base salary range for this position is $142,500.00 - $206,700.00, depending on factors such as experience, education, level, skills, and location. This range is based on a full-time position. In addition to base salary, this role is eligible for incentive compensation. Moody's also offers a competitive benefits package, including not but limited to medical, dental, vision, parental leave, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, a discounted employee stock purchase plan, and tuition reimbursement.