Assistant Director Manager - Product Management

Moody's Corporation; Brussel Hoofdstad; On-site; EUR 90,000 - 130,000; Full time

Job summary

Moody’s Corporation is seeking a senior Data Product Manager to lead a business-critical data platform powering enterprise analytics. You will own a data engineering squad, drive roadmap and delivery, and collaborate with governance, QA, and product teams to deliver new datasets and AI-ready capabilities.

You will balance speed, scalability, and cost while ensuring data quality and governance. Strong communication and stakeholder management are essential in this role within Moody’s collaborative

Qualifications

• Bachelor’s degree in a related field is required.
• Advanced degree (MBA/MS) preferred.
• 5+ years of experience in technical product management or data engineering.
• Experience with data platforms, warehousing, and analytics technologies.

Responsibilities

• Lead the delivery, reliability, and evolution of a business-critical data platform used enterprise-wide.
• Own a data engineering squad; drive roadmap planning, prioritization, and delivery of platform capabilities.
• Partner with Governance, QA, Data Engineering, and Product teams to deliver new data sets and enhance assets.
• Collaborate with engineering to balance speed, scalability, cost, and AI readiness.
• Lead agile execution: sprint planning, backlog refinement, reviews, and delivery tracking.
• Own and prioritize backlogs of stories, defects, and production support requirements.
• Utilize AI and generative AI tools to accelerate requirements, analysis, and reporting.
• Embed data quality, lineage, governance, and controls in product requirements for AI-enabled solutions.
• Drive coordination across teams to manage dependencies, releases, and readiness.
• Monitor platform health, availability, data freshness, and operational performance.

Skills

Tech product mgmt

Data engineering

Agile methods

Data platforms

SQL proficiency

Incident mgmt

AI concepts

Stakeholder mgmt

Education

Bachelor’s degree

Advanced degree preferred

Tools

Snowflake

Databricks

Redshift

Athena

Kafka

Job description

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.

Skills and Competencies

• 5+ years of experience in technical product management or data engineering for data-intensive B2B products
• Strong understanding of agile methodologies, product delivery frameworks, backlog management, and cross-functional delivery practices
• Experience working with data platforms, data warehousing, and analytics technologies such as Snowflake, Databricks, Redshift, Athena, Kafka, or similar technologies
• Proficiency with SQL for data analysis, troubleshooting, validation, and data-driven decision making
• Experience managing business-critical data platforms, including incident management, production support coordination, operational monitoring, and service level objective management
• Strong communication, analytical, and stakeholder management skills with the ability to translate complex technical concepts into business value
• Results-oriented mindset with a demonstrated ability to drive delivery, influence outcomes, and improve organizational effectiveness in matrixed environments
• 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 in Computer Science, Information Systems, Engineering, Data Science, Business, or a related field
• Advanced degree such as a Master’s degree or Master of Business Administration preferred

Responsibilities

Lead the delivery, reliability, and evolution of a business-critical data platform that powers data products and analytics across the enterprise.

• Own a data engineering squad and drive roadmap planning, prioritization, execution, and delivery of platform capabilities and data products
• Accelerate decision-making, remove delivery obstacles, and ensure the team remains focused on high-value outcomes for customers and the business
• Partner with Data Governance, Quality Assurance, Data Engineering, and Product Development teams to deliver new data sets and enhance existing data assets
• Collaborate with engineering teams to assess solution complexity, evaluate architectural tradeoffs, and balance speed, scalability, cost, and AI readiness
• Lead agile execution through sprint planning, backlog refinement, reviews, retrospectives, and delivery tracking
• Own and prioritize a backlog of user stories, defects, refactoring activities, infrastructure initiatives, and production support requirements based on business value and risk reduction
• Utilize AI and generative AI tools to accelerate requirements development, stakeholder analysis, issue investigation, prioritization decisions, and operational reporting
• Embed data quality, lineage, governance, and controls within product requirements and acceptance criteria, particularly for data supporting AI-enabled solutions
• Drive coordination across engineering, operations, governance, and downstream product teams to manage dependencies, releases, and production readiness
• Own platform health, availability, data freshness, and operational performance through partnership with production support and operations teams
• Serve as an escalation point during production incidents, leading root‑cause analysis, remediation planning, and post‑incident reviews
• Define and monitor service level agreements and service level objectives for platform availability, data quality, and operational performance
• Proactively identify and mitigate delivery, operational, quality, privacy, and governance risks throughout the data lifecycle
• Build strong relationships with business stakeholders and data strategy teams to support the long‑term evolution of enterprise data capabilities

About the Team

Our Data Product Management team is responsible for delivering high-quality, trusted, and scalable data platforms that power analytics, products, and decision‑making across Moody’s. The team partners closely with engineering, data governance, quality assurance, operations, and product development teams to bring new data capabilities to market while maintaining world‑class standards for data quality, resiliency, and operational excellence. By joining this team, you will play a key role in shaping enterprise data infrastructure, enabling AI‑ready data products, and driving impactful outcomes across a highly collaborative and innovative environment.

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.