Job details
Skills and Competencies
- Proven experience in technical product management or data engineering for data‑intensive B2B platforms
- Strong understanding of agile delivery methodologies, backlog management, and iterative development
- Deep familiarity with modern data platforms and architectures, including data warehousing, streaming, and analytics environments
- Ability to collaborate effectively with data engineers to evaluate architectural tradeoffs across scalability, cost, performance, and AI readiness
- Hands‑on proficiency with SQL for data analysis, validation, and troubleshooting
- Experience defining, embedding, and operationalizing data quality, controls, lineage, and governance standards
- Working knowledge of how data is consumed by analytics, machine learning, and AI‑driven products
- Strong analytical and problem‑solving skills with high attention to detail
- Results‑oriented mindset with the ability to drive delivery in complex, matrixed environments
- Excellent communication skills, able to translate complex technical concepts for both technical and non‑technical stakeholders
- Demonstrated initiative, curiosity, and commitment to continuous improvement and scalable ways of working
Education
- Bachelor’s degree required; advanced degree such as an MBA or Master’s degree is a plus
Responsibilities
This role owns the delivery and evolution of a core data platform, leading a data engineering squad to rapidly and reliably bring high‑quality, well‑governed data products to market.
- Own a data engineering squad with accountability 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 Data Platform Product Owners, Data Governance, Quality Assurance, Data Engineering, and internal Product Development teams to deliver new data sets
- Collaborate closely with engineers to understand solution complexity and select implementation approaches that balance speed, scalability, cost, and AI readiness
- Lead agile ceremonies including sprint planning, backlog refinement, reviews, and retrospectives to ensure consistent, high‑quality execution
- 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 initiatives, and production support based on business value, reuse, risk reduction, and AI enablement
- Apply AI and Generative AI tools to accelerate requirements creation, summarize stakeholder input, and support prioritization and impact analysis
- 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 drive adoption and evolution of data assets
- Embed data quality, lineage, and governance standards into backlog items and acceptance criteria, with particular focus on AI and model‑driven use cases
- Proactively identify and mitigate delivery, quality, privacy, and operational risks across the data lifecycle
About the Team
The Data Product Management Team is a dynamic, analytical group within Moody’s Analytics that combines deep curiosity about data with a strong focus on delivering measurable value. The team partners closely with engineering, governance, and product stakeholders to ensure that core data platforms are reliable, scalable, and ready to support advanced analytics and AI‑driven solutions.
