Lead Technical Product Manager

Consumer Product and Innovation (CP&I) Data and Analytics Engineering sits at the intersection of product innovation and enterprise data strategy at Nike. Reporting to the Engineering Director, this team partners with data scientists, engineers, analysts, and product managers to build a cross-capability data foundation and a semantic layer that powers Advanced Analytics, Business Intelligence, and AI solutions driving business growth. WHO WE ARE LOOKING FOR We're looking for a Lead Technical Product Manager to own the BI and analytics product strategy within Nike's CP&I organization. This role serves as the insights product leader for CP&I's primary capability areas - Merchandising, Apparel Product Creation, and Footwear Product Creation - ensuring a single semantic layer drives consistent metrics and KPIs across workflow and operations in every modality and surface area. The candidate will be the accountable product owner for curating the governed metric catalog, prioritizing the metric roadmap against FY plan commitments, and surfacing metric gaps before they block business decisions. We're seeking someone who is fluent in the metrics and data that drive decisions for every persona in their domain, and who can partner deeply with capability product managers, business users, and analytics engineering peers to deliver one consistent semantic data model and metrics catalog. The ideal candidate brings strong product leadership, technical fluency across modern analytics platforms, and the ability to translate complex business workflows into clear product requirements. Success in this role requires exceptional stakeholder management, a data-driven mindset, and the ability to coordinate delivery across concurrent tool rollouts and enterprise consumers. Bachelor's degree or equivalent combination of education, experience, or training 5+ years of experience in product management, analytics product ownership, or business intelligence, with demonstrated expertise in metrics governance and semantic layer strategy Proven experience curating metric catalogs, defining KPIs, and driving analytics delivery across multiple tools and modalities (e.g., Tableau, Databricks, Web applications) Strong partnership skills with cross-functional stakeholders including product managers, engineering teams, and business users across complex, matrixed organizations Experience assessing data impact, sequencing analytics rollouts, and aligning metric roadmaps to named business outcomes and capability delivery timelines Preferred qualifications: Experience with Databricks Lakehouse, Databricks Metrics Views, Databricks Unity Catalog or similar governed data catalog platforms Familiarity with retail consumer product creation and merchandising workflows Experience influencing product strategy and driving alignment across multiple stakeholders in a technical analytics or data product environment WHAT YOU'LL WORK ON You'll shape how Nike's CP&I organization measures, decides, and delivers - owning the product vision and roadmap for a governed metric catalog and semantic layer that brings consistency to analytics across Merchandising, Design, and Development. This is strategic, cross-functional product leadership at the intersection of business outcomes and enterprise data platforms. Own metric catalog curation and governance – disposition metrics across Tableau, Smartsheet, Airtable, and Excel, and activate a governed catalog through Unity Catalog with explicit keep, adapt, and deprecate decisions Drive metric prioritization and roadmap ownership, sequencing which metrics matter most against FY plan commitments, release cycles, and capability delivery outcomes in partnership with capability product managers and business stakeholders Identify metric gaps for emerging strategies before they block decisions, and co-author new metric definitions with the business as the entry point for analytics engineering work Assess input data impact for new or changed capability data - determining whether requirements extend existing Product Data Foundation entities or require new attributes, and surfacing dependencies across enterprise KPIs and data domains Define analytics delivery modality strategy - deciding where each metric is served from (Tableau, Databricks, Web applications), what actions it drives, and eliminating bespoke, inconsistent calculations Coordinate cross-tool sequencing and timing for metric and modality changes across concurrent tool rollouts and business-process shifts with downstream consumers Partner with data and analytics engineering and capability product managers to deliver prioritized metric roadmaps tied to named business outcomes We offer a number of accommodations to complete our interview process including screen readers, sign language interpreters, accessible and single location for in-person interviews, closed captioning, and other reasonable modifications as needed. 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