Data Products & Metrics Foundation Lead - Wallet, Payments & Commerce

Apple Apple · Big Tech · Cary +1 · Software and Services

This role focuses on architecting the future of data consumption for Apple's Wallet, Payments & Commerce, specifically shaping the metrics foundation, headless BI, and AI-driven insights strategy. The goal is to drive alignment, standards, and long-term architecture for data modeling, access, and consumption, enabling AI-assisted insights and LLM-powered analytics.

What you'd actually do

  1. Design and own the metrics layer — defining how metrics are modeled, governed, and consumed across the organization
  2. Architect and implement a headless BI strategy decoupling metric definitions from visualization/consumption tools
  3. Build and maintain a centralized metrics store ensuring single source of truth for all KPIs and business metrics
  4. Own the future-state visualization strategy — including self-serve, embedded analytics, and AI-assisted insights
  5. Serve as the BI Solution Architect — evaluating, selecting, and governing visualization and reporting tools

Skills

Required

  • Bachelor's or Master's degree in Computer Science or a related technical field or equivalent experience
  • 10+ years of experience in designing, developing and deploying next-gen Analytical Data Products
  • 3+ years in a lead, architect, or senior IC role in Metrics foundation and BI solution design
  • Strong understanding of data warehousing, data modeling (dimensional/star schemas), and metric standardization
  • Experience implementing or working with headless BI / semantic layer tools
  • Demonstrated ability to influence without authority across engineering and business teams
  • Excellent Executive communication skills with both technical and non-technical audiences

Nice to have

  • Familiarity with payments, commerce, or fintech data — transaction metrics, funnel analytics, financial KPIs
  • Familiarity with AI-driven analytics / conversational BI
  • Knowledge of data governance, data cataloging, and metadata management
  • Strong SQL skills, with exposure to Python and large-scale data processing frameworks (e.g., Apache Spark)
  • Experience working closely with data engineering and platform teams to align on data models, and infrastructure/platform requirements
  • Experience navigating complex organization dynamics and driving cross-functional initiatives to completion in a fast-paced environ

What the JD emphasized

  • AI-driven insights strategy
  • AI-driven decision intelligence
  • AI-assisted insights
  • AI-driven data consumption model
  • LLM-powered analytics
  • AI assistants

Other signals

  • AI-driven insights strategy
  • AI-driven decision intelligence
  • AI-assisted insights
  • AI-driven data consumption model
  • LLM-powered analytics
  • AI assistants