Principal HR Product Manager, Workforce Intelligence

Role Summary

We are building a modern AI-enabled HR organization where data and intelligence are embedded into every product workflow and decision.

The Principal Product Manager Workforce Intelligence is responsible for defining the vision and driving the strategy for how HR data is structured governed analyzed and delivered across the enterprise. This is ahigh-impact high-influence positionfor someone who leads through expertise vision and the ability to align teams around a shared direction.

This role owns the product strategy for the full HR intelligence stackfrom the foundational data architecture that makes reliable analytics possible to the reporting systems that drive operational decisions to the AI-powered tools that put predictive insight directly in the hands of managers HR partners and leaders. The Principal PM will serve as the connective tissue betweenHR functional teams(Talent Acquisition Talent Management Total Rewards Employee Experience and People Operations etc.) and thetechnical teamsData Engineering HR Technology and People Analyticswho build and maintain these capabilities.

Success in this role is measured by the clarity of the vision set the quality of the products built and the degree to which data and intelligence change how HR operates across the company.

How This Role Works

This roleoperates at the intersection of business strategy and technical executiontranslating HR priorities into product direction and influencing what gets built in what order and to what standard.

The Principal PM will:

• Set theproduct vision and roadmapfor HR Workforce Intelligence
• Influence and alignData Engineering People Analytics and HR Technology teams around that vision
• Partner with HR functional leaders to understand their data needs and translate them into scalable product solutions
• Work hand-in-hand with theDirector of People Analyticsto ensure strategy and execution are tightly connected
• Drive decisions throughclarity credibility and structured thinking

Key Responsibilities

Enterprise HR Data Foundation

Define the product strategy for the underlying data infrastructure that makes all HR analytics trustworthy and scalable. This includes:

• Establishing the vision for theenterprise HR data architecturehow data flows from source systems how it is modeled and how it is made available for consumption across products and teams
• Driving alignment onsystem integrationsbetween HR platforms ensuring that data moving between systems is consistent complete and reliable
• Owning theanalytics semantic layerstrategythe standardized definitions business logic and governed metrics that ensure every team is working from a single trusted source of truth
• Leading the strategy and evaluation process for thereporting platform infrastructure for how HR data is accessed and delivered at scale

Establish Trusted Scalable Reporting

Ensure the organization has well-governed reliable reporting that supports both operational rhythms and strategic decision-making. This includes:

• Definingfoundational HR metricsthe core set of workforce KPIs that anchor all reporting and are consistently understood across HR and the business
• Setting the product direction for theoperational reporting cadence including the data products and pipelines that support Weekly Business Reviews (WBRs) Quarterly Business Reviews (QBRs) and executive-level reporting
• Driving the strategy for products like performance reporting suitethat gives leaders HR partners and managers consistent trusted visibility into workforce outcomes and glidepath reportingto track progress against workforce targets and strategic workforce plans over time

Champion Employee Data Quality and Governance

Define the product standards that ensure employee data is accurate governed and trustworthy as the foundation for all downstream analytics. This includes:

• Setting the strategy foremployee data managementhow employee records are created maintained and trusted as the authoritative source across HR products
• Influencing theHCM platform and HR Technology teamson data ownership governance standards and how employee data administration processes are designed and maintained
• Establishing product principles and standards fordata quality access controls and sensitive data protectionacross all HR data productsbalancing broad access to insight with rigorous protection of personal and sensitive information

Scale Self-Service and Insight Delivery

Build the frameworks and products that enable HR partners managers and business leaders to access data and insights without creating a centralized bottleneck. This includes:

• Owning theself-service reporting platform strategydefining the right tools interfaces and access tiers that allow HR Business Partners and business leaders to answer their own questions confidently and independently
• Driving the development of anHRBP Toolkita curated suite of data products dashboards and intelligence resources that enable HR Business Partners to show up to business conversations with consistent high-quality insight
• Defining and advocating for adelivery modelthat scales analytical capacity across the HR organization ensuring that insight reaches the people who need it without requiring every request to flow through a central team
• Establishing the principle that insights should be deliveredin workflow and in contextembedded in the tools people already use not in disconnected reports or portals

Define and Drive the AI and Predictive Analytics Roadmap

Lead the vision for how AI and predictive modeling transform the way HR operates and how people decisions are made across the company. This includes:

• Identifying prioritizing and sequencingAI use cases across HR with a focus on areas such as workforce planning retention risk talent forecasting organizational health and manager effectiveness
• Defining the product requirements and business outcomes forAI-powered decision support toolsthat give managers and HR leaders proactive forward-looking intelligence
• Partnering withData Engineering and People Analyticsto ensure that predictive models and intelligent systems are built to the right specifications and deployed in ways that drive real behavioral change
• Championing the integration of AI capabilities intoexisting HR workflowsso that intelligence feels like a natural part of how work gets done not a separate tool that requires extra effort to access

Raise the Bar for Data-Driven Decision-Making Across HR

Operate as a standards-setter and thought leader for how HR uses datawithout owning execution or centralizing work. This includes:

• Acting as atranslator between the business and technical teams turning functional pain points and strategic priorities into clear product requirements that Data Engineering People Analytics and HR Technology can execute against
• Helping HR functional teamsraise their own data fluencyand adopt new products and capabilities as they are built
• Defining what good looks like formetrics definitions analytical rigor experimentation design and data storytellingacross HR products and teams

Qualifications

Must Have:

• 10 years in product management data products or analyticswith demonstrated ownership of complex cross-functional initiatives as an individual contributor
• Proven ability toinfluencedriving alignment and action across engineering analytics and business teams through clarity credibility and structured thinking
• Deep analytical fluency: comfortable with data architecture concepts metrics frameworks semantic layers and model-driven products
• Track record of translating ambiguous high-stakes business problems into structured product strategies and roadmaps
• Experience partnering withboth technical teams and business stakeholdersable to move fluidly between conversations about data pipelines and conversations about talent strategy

Strongly Preferred:

• Experience building and scalingdata platforms analytics products or AI-enabled toolsin an enterprise environment
• Background inHR technology people analytics or workforce intelligence
• Familiarity withHCM platforms data governance practices and analytics semantic layer concepts
• Experience applyingresponsible AI principles including bias assessment model explainability and data privacy in a people data context
• Experience working in or closely withHR functional domainssuch as Talent Acquisition Talent Management or Total Rewards