Data Project Manager
- NEW YORK, NY, United States
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Job details
- Posting language
- English
- Posted
Original job description
12461 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 * Employment eligibility to work in the United States is required, as Moody's will not pursue visa sponsorship for this position * Hands-on experience with SQL and comfort querying and analyzing large datasets across relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., DynamoDB, MongoDB) * Strong track record of partnering with data engineers and navigating complex data infrastructure to deliver scalable, high-quality data solutions * Experience working in agile development environments and leading sprint planning, stand-ups, and retrospectives to support iterative product delivery * Effective communication skills with the ability to bridge technical and non-technical stakeholders across product, engineering, QA, and business teams * Results-oriented mindset, using metrics and client feedback to prioritize work, measure impact, and drive continuous improvement * Experience within the finance industry, with an understanding of the importance of data quality, timeliness, and regulatory alignment * Proactive and collaborative team member who promotes automation, scalability, and operational efficiency throughout the data product lifecycle * Basic understanding of artificial intelligence concepts, with curiosity and enthusiasm for learning how AI tools can be used to improve processes and drive efficiency, and an interest in developing awareness of responsible AI practices, including risk management and ethical useEducation * Bachelor's degree required, preferably in a quantitative or technical disciplineResponsibilities The Data Product Manager owns the end-to-end delivery of scalable data products, partnering with cross-functional teams to support analytical workflows and enterprise data delivery across Moody's Analytics. * Lead the delivery of data products in collaboration with data engineering, QA, technology, and business strategy teams * Translate business needs into clear data requirements with a strong focus on data workflows, scalability, and performance * Own and manage the data product backlog, prioritizing features, technical tasks, and enhancements based on business value, effort, and dependencies * Partner closely with engineering teams to ensure accurate understanding of data structures, source systems, and integration logic * Actively manage sprint planning, stand-ups, and retrospectives within an agile development environment * Ensure data quality, documentation, lineage, and governance standards are consistently upheld * Identify opportunities to automate data workflows and reduce operational risk and failure points across the data lifecycle * Communicate product status, risks, dependencies, and decisions to stakeholders in a clear and timely mannerAbout the TeamThe Digital Content and Innovation team is responsible for managing Moody's flagship research, data, and analytical platforms,
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Skills
- Hazard assessment
- Data engineering
- Prioritization
- Agile development
- Documentation
- Research