Apple
Lead iCloud Insights Engineer, Services Data Science & Analytics
$167K–$312K
Austin, Texas +2 · Full-time · Posted Sep 1, 2026
- Location
- Austin, Texas
Culver City, California
Cupertino, California - Experience
- 8+ years; experience in Data Visualization, Data/Analytics Engineering, Data Science, or Software Engineering, with demonstrated progression into more senior or technical-lead scope.
- Education
- BS in Computer Science, Statistics, Mathematics, Information Systems, Engineering, Economics, or a related field.
About the job
Leads the strategy and development of AI-assisted, full-stack data applications and insights products that help Apple teams understand iCloud performance and make business decisions.
What you'll do
- Build AI-assisted web applications, executive reporting tools, and self-service data products that turn large-scale data into actionable insights.
- Partner with Data Science and business teams to define metrics, design datasets, and develop AI-driven automation and pipelines.
- Set technical direction, mentor engineers, and lead cross-functional projects from architecture through delivery.
What they ask for
- 8+ years in Data Visualization, Data/Analytics Engineering, Data Science, or Software Engineering, with progression into senior or technical-lead scope.
- Hands-on experience building and deploying custom web applications and integrating AI/LLM capabilities into applications or workflows.
- Strong SQL skills and experience designing data models and pipelines for responsive, interactive applications.
- BS in Computer Science, Statistics, Mathematics, Information Systems, Engineering, Economics, or a related field.
Nice to have
- Experience with digital subscriptions, large-scale e-commerce, or media streaming platforms.
- Strong Python skills, AI/ML libraries, and Spark for large-scale data processing.
Pay
$175,500 to $311,700 USD base salary; $166,600 to $296,000 USD base salary
Tools
React, Streamlit, Flask, Django, Next.js, SQL, Python, Spark
AI focus
Build AI-assisted applications and pipelines, including natural language querying, automated insight generation, intelligent summarization, and agentic workflows.
Model-written summary · the original posting is authoritative