Drimva

Apple

Data Products & Business Intelligence Lead - Wallet, Payments & Commerce

$216K–$325K

Austin, Texas +2 · Full-time · Posted Sep 17, 2026

Location
Austin, Texas
Cary, North Carolina
Cupertino, California
Experience
10+ years in data and AI-powered analytical products; 3+ years as a senior IC leading data products, AI-enabled analytics, and visualizations across multiple lines of business.
Education
Bachelor’s or Master’s degree in Computer Science or a related technical field or equivalent experience.

About the job

Leads the design and delivery of scalable, privacy-first analytics data products, metrics, and visualizations for Apple Wallet, Payments & Commerce.

What you'll do

  • Define instrumentation and user journeys, and build and maintain analytical datasets, data products, and metrics layers.
  • Establish data quality frameworks and develop visualizations and decision tools, including AI-enabled analytics.
  • Gather and translate partner requirements into product specifications, lead discovery workshops, and mentor junior team members.

What they ask for

  • Bachelor’s or Master’s degree in Computer Science or a related technical field, or equivalent experience.
  • 10+ years designing, developing, and deploying data and AI-powered analytical products; 3+ years as a senior IC leading data products, AI-enabled analytics, and visualizations across multiple lines of business.
  • Strong proficiency in SQL, Scala, and Python; hands-on experience with data pipeline tools, CI/CD practices, and version control.
  • Experience with Generative AI/LLMs and agentic AI patterns for analytics; strong understanding of data warehousing, dimensional modeling, semantic/metrics layers, and metric standardization.

Nice to have

  • Familiarity with digital payments or fintech data and AI-driven analytics or conversational BI.
  • Knowledge of data governance, data cataloging, and metadata management.

Pay

$216,200 and $324,800 USD base salary

Tools

SQL, Scala, Python, Apache Spark, Kafka, Airflow, Generative AI/LLMs

AI focus

Applies Generative AI/LLMs and agentic AI patterns to analytics, including insight generation, natural-language data exploration, workflow automation, and AI-driven inferences and visualizations.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 5, 2026 (UTC)