VP-Data Engineer (People Analytics)

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 8+ years of experience in data engineering, analytics engineering, platform engineering, or related disciplines Deep expertise in SQL, data modeling, and data architecture with proven ability to design scalable, reusable data structures Experience building and operating modern cloud data platforms and lakehouse architectures Strong understanding of data pipeline orchestration, testing, monitoring, and reliability practices Experience implementing data governance, metadata management, lineage tracking, and data quality frameworks Ability to translate business concepts and workforce requirements into scalable technical data structures and governed data assets Experience with Workday data extraction (RaaS, WQL, Core Connectors) and effective-dated HCM data models is preferred; familiarity with semantic layers, knowledge graphs, or AI-ready data architectures is a plus Experience with Microsoft Fabric, Azure Data Platform, Databricks, Power BI semantic models, or similar technologies is preferred Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using AI tools to lead innovation initiatives. Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization Education Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field required; advanced degree preferred Responsibilities Design and operate the enterprise People data platform that powers workforce analytics, AI-enabled insights, and data-driven People solutions at Moody's. Design and maintain the People Analytics lakehouse and data architecture, ensuring platform performance, entitlements, reliability, observability, and operational excellence Develop, monitor, and optimize data ingestion and transformation pipelines from HR, talent, learning, engagement, compensation, and related source systems Build and maintain canonical datasets — including the enterprise worker spine and governed workforce facts — serving as the authoritative sources of truth for workforce data across the People function Establish consistent data models, metric definitions, metadata, business rules, and semantic layers that can be reused across multiple analytics and AI use cases Implement data quality testing, lineage tracking, monitoring, and certification processes to ensure workforce data remains secure, compliant, and audit-ready Partner with People Data Product Owners to translate business requirements into scalable, well-documented data assets that support reporting, analytics, AI assistants, and future workforce applications Collaborate with Privacy, Risk, Legal, Security, and Technology teams to ensure appropriate governance standards, documentation, version control, and change tracking for