Jobs Companies Nike Lead Data and Analytics Insights Analyst

À propos de ce poste Lead Data and Analytics Insights Analyst chez Nike

Nike · Sur site · Beaverton, Oregon

LEAD, DATA AND ANALYTICS INSIGHTS ANALYST - NIKE

[Beaverton, OR - USA]

WHO YOU'LL WORK WITH

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 Data and Analytics Insights Analyst 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 - establishing the KPI framework and decision intelligence strategy that drives how Merchants, Product Designers and Developers measure performance across workflow and operations in every modality.

The candidate will own the governed KPI catalog and semantic layer, identifying decision points lacking performance visibility and defining the KPIs, benchmarks, and leading indicators required to measure emerging business capabilities. We're seeking someone who can perform applied metric modeling and validation, partner deeply with Capability Product Managers, business users, and analytics engineering peers, and translate governed metrics into decision-ready narratives for executives and cross-functional audiences.

The ideal candidate brings strong product leadership, technical fluency across modern analytics platforms, and the ability to connect Merchandising, Product Design, and Development performance into integrated business scorecards. 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 data science, data analytics 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 KPI frameworks, metrics governance, semantic layer strategy, and applied analytics
  • Proven experience curating metric catalogs, defining KPIs, validating metric logic, and driving analytics delivery across multiple tools and modalities (e.g., Tableau, Databricks, Custom Apps)
  • Strong partnership skills with cross-functional stakeholders including Capability Product Managers, analytics engineering teams, and business users across complex, matrixed organizations
  • Experience assessing data impact, defining analytics requirements, sequencing rollouts, and aligning insights roadmaps to named business outcomes and decision-making needs

Preferred qualifications:

  • Experience with Unity Catalog, Databricks Lakehouse, or similar governed data catalog platforms
  • Familiarity with Nike or retail/consumer product creation and merchandising workflows
  • Experience with executive storytelling, cross-domain performance integration, and influencing product strategy 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 KPI framework, governed metric catalog, and semantic layer that brings consistency to analytics across Merchandising, Product Design, and Product Development. This is strategic, cross-functional product leadership at the intersection of business outcomes and enterprise data platforms.

  • Own the KPI framework and metric catalog curation and governance - inventory metrics across Tableau, Smartsheets, Airtable, and Excel, and activate a governed catalog and semantic layer with standardized metric definitions, business rules, and explicit keep, adapt, and deprecate decisions
  • Establish decision intelligence strategy - defining the KPIs, performance frameworks, and analytic questions that guide decisions and surfacing metric gaps for emerging strategies before they block decisions
  • Perform applied metric modeling and validation - statistical sanity-checking, trend and outlier analysis, and scenario testing of proposed KPI formulas against historical data to prove metric logic
  • Contribute to metric prioritization and roadmap ownership, sequencing KPIs, scorecards, and insights that most influence business outcomes and drive backlogs for analytics engineering teams
  • Define cross-workflow analytics requirements and assess input data impact - determining whether new capability data exists in Nike’s Product Data Foundation or requires new attributes, and surfacing dependencies across enterprise KPIs and data domains
  • Own analytics delivery strategy - deciding how insights are surfaced across modalities, so the right metrics, context, and actions reach the right persona at the right moment
  • Connect Merchandising, Product Design, and Product Development performance into end-to-end integrated scorecards, and translate governed metrics and analysis into clear, decision-ready narratives for executives and cross-functional audiences

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. If you discover, as you navigate our application process, that you need assistance or an accommodation due to a disability, please complete the Candidate Accommodation Request Form.

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À propos de Nike

At NIKE, Inc. we promise to provide a premium, inclusive, compelling and authentic candidate experience. Delivering on this promise means we allow you to be at your best — and to do that, you need to understand how the hiring process works. Transparency is key.

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