below marketmost similar roles pay hereabove market
This role pays more than
65%
of similar roles. Most pay
$159,525–$241,750
— the blue band above.
At the midpoint, this role pays about
$231k
versus about
$201k
for comparable roles.
Based on 240 similar postings.
Employer
About Apple Inc
Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
Apple Inc currently has
3497 open roles
on FindRole.
Listed pay typically runs
$174,149–$277,600
across 2702 roles with salary data.
The Lead iCloud Insights Engineer, Services Data Science & Analytics, joins the Services Data Science & Analytics team to own the data product and application strategy for iCloud. This role involves designing and building custom, AI-assisted full-stack web applications that transform internet-scale data into interactive, actionable insights for business and engineering partners. You will develop next-generation executive reporting solutions and self-service products by integrating AI/LLM capabilities like natural language querying, automated insight generation, and agentic workflows. Key technologies include Python, SQL, Spark, and frameworks such as React, Streamlit, Flask, Django, or Next.js. You will also utilize AI/ML libraries like LangChain and OpenAI APIs. The work focuses on improving e-commerce and media streaming services by defining metrics, designing datasets, and building automated pipelines to drive informed decision-making.
Own and drive the data product and application strategy for iCloud services.
Design and build full-stack web applications to make internet-scale data interactive and actionable.
Integrate AI and LLM capabilities like natural language querying and automated insight generation into data products.
Partner with Data Science peers to define metrics, design datasets, and develop automated data pipelines.
Architect and deliver next-generation executive reporting solutions and self-service data products.
Set technical direction and best practices for application development while mentoring other engineers.
Lead complex, cross-functional projects from initial architecture and planning through final execution and delivery.
What we're looking for
BS in Computer Science, Statistics, Mathematics, Information Systems, Engineering, Economics, or a related field.
MS in Computer Science, Statistics, Mathematics, Information Systems, Engineering, Economics, or a related field (preferred).
8+ years of experience 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 using frameworks like React, Streamlit, Flask, Django, Next.js, or similar.
Practical experience integrating AI/LLM capabilities into applications or workflows, such as RAG, AI agents, or automated insight generation.
Strong SQL skills and experience designing data models and pipelines to support responsive, highly interactive applications.
Proficiency with data visualization tools and familiarity with data engineering tools, pipeline development, and aggregation strategies at scale.
Excellent communication, presentation, and stakeholder management skills with a proven ability to lead projects independently and mentor other engineers.
Experience in a digital subscription business or large-scale e-commerce or media streaming platform (preferred).
Strong Python skills, including experience with AI/ML libraries and Spark for large-scale data processing (preferred).
Experience designing and building AI agents or agentic workflows for internal tooling or analytics automation (preferred).
Track record of leading a team or driving technical strategy through a tool migration or major architectural shift (preferred).
Familiarity with cloud-native application deployment and modern front-end/back-end development practices (preferred).
Java
Swift
C++
Go
Kubernetes
Distributed Systems
Observability
Data Encryption
Secure Key Management
Security Architecture
Performance Benchmarking
Debugging