VP-Data Engineer (People Analytics)

Moody; New York (NY); On-site; USD 192,000 - 278,000; Full time

Job summary

Moody's is seeking a senior data engineering leader to design and operate the enterprise People data platform powering workforce analytics, AI-enabled insights, and data-driven People solutions. You will lead the People Analytics lakehouse, ensure data quality, governance, and scalable data assets, partnering with HR, Privacy, Risk, Legal, and Technology teams across Moody's global operations.

This role emphasizes building reusable data patterns, lineage, and semantic layers to accelerate

Qualifications

• 8+ years of experience in data engineering, analytics engineering, platform engineering, or related disciplines.
• Deep expertise in SQL, data modeling, and data architecture.
• 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.
• Experience with Workday data extraction and AI-ready architectures 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 is preferred.
• Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions.

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 all workforce data.
• Create reusable patterns and foundational data layers that reduce fragmented reporting, eliminate duplicate data preparation, and accelerate solution development across the People function.

Skills

SQL

Data modeling

Data architecture

Cloud data platforms

Data governance

AI strategy

Education

Bachelor's degree in Computer Science or related field

Tools

Workday data extraction

Azure Data Platform

Databricks

Power BI semantic models

Microsoft Fabric

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

• 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 all workforce data
• Create reusable patterns and foundational data layers that reduce fragmented reporting, eliminate duplicate data preparation, and accelerate solution development across the People function

About the Team

The People Analytics team at Moody's is building an AI-native workforce intelligence capability grounded in trusted, governed data. Our mission is to establish a reliable, enterprise-grade data foundation that enables meaningful workforce analytics, AI-powered decision-making, and innovative People data products. We partner closely with HR, Technology, Legal, and business leaders to ensure our data platform is secure, scalable, and purpose-built to support the evolving needs of a global workforce. By joining our team, you will be at the center of a transformative initiative that combines cutting-edge data platform engineering with people strategy — helping Moody's leaders navigate the future of work with clarity, speed, and confidence.

For US-based roles only: the anticipated hiring base salary range for this position is$191,500.00-$277,600.00, 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.

Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, gender, age, religion or creed, national origin, ancestry, citizenship, marital or familial status,sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, military or veteran status, or any other characteristic protected by law. Moody’s also provides reasonable accommodation to qualified individuals with disabilities or based on a sincerely held religious belief in accordance with applicable laws. If you need to inquire about a reasonable accommodation, or need assistance with completing the application process, please email [e-mail] . This contact information is for accommodation requests only, and cannot be used to inquire about the status of applications

For San Francisco positions, qualified applicants with criminal histories will be considered for employment consistent with the requirements of the San Francisco Fair Chance Ordinance.

This position may be considered a promotional opportunity, pursuant to the Colorado Equal Pay for Equal Work Act.

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.