Sr. Data Engineer, iCloud Insights Engineering

Apple Inc.; Cupertino (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

Apple Services Data Science & Analytics iCloud Insights Engineering is seeking a Data Engineer to work with massive internet-scale iCloud data across product and customer touchpoints. You will design scalable pipelines, build robust data models, and ensure high-quality data for decisions while respecting privacy and regulatory policy.

You will collaborate closely with insights engineering and data science peers, driving automation, reliability, and clear reporting across iCloud data domains

Qualifications

• 5+ years building and maintaining complex data pipelines at scale.
• Proficient in SQL with large internet-scale datasets.
• Strong Python or similar languages and Spark experience.
• Experience with data modeling and analytics reporting.
• Excellent written and verbal communication for diverse stakeholders.
• Able to manage multiple projects with competing priorities.
• BS in CS, Statistics, Math, IS, Engineering, Economics, or related field.

Responsibilities

• Build and maintain data infrastructure powering iCloud insights across product and customer touchpoints.
• Design data models and scalable pipelines for reliable analytics data.
• Collaborate with insights engineering and data science teams to translate requirements.
• Improve automation and reliability of core iCloud data workflows.
• Surface patterns across iCloud storage, subscription, engagement, and commerce data.

Skills

SQL

Python

Spark

Data modeling

Data pipelines

Communication

Time management

Education

BS in Computer Science or related field

MS in Computer Science or related field

Tools

Spark

Job description

Austin, Texas, United States Software and Services

Are you ready to make a significant impact at the intersection of data engineering and iCloud analytics within Apple? If you are passionate about building robust data pipelines, crafting complex data models, and enabling compelling, data-driven insights at scale, The Apple Services Data Science & Analytics organization drives decisions that improve the customer experience, accelerate growth, and uncover new business opportunities while respecting user privacy and adhering to regulatory policy.

Description

We work on some of the largest e-commerce and media streaming businesses in the world and have an incredible team collaborating on the best ways to improve these services for our customers! Our culture is built on rapid iteration, open debate, and independent thinking — we take calculated risks and work as analytical advisors across product, design, engineering, marketing, editorial, legal, and business teams.

Responsibilities

• As a Data Engineer on the Services Data Science & Analytics iCloud Insights Engineering team, you will work with massive internet-scale iCloud data across numerous product and customer touchpoints.
• You will heavily contribute to and maintain the data infrastructure that powers iCloud insights — building and optimizing pipelines, designing data models, and ensuring that both DS&A and stakeholder teams have reliable, high-quality data to drive business decisions.
• A great fit for this role communicates and collaborates well across many different teams, has an agile approach to solving challenging problems quickly, and stresses the details.
• You will partner closely with insights engineering and data science peers to understand requirements and translate them into scalable data solutions, improving the automation and reliability of core iCloud data workflows.
• Your work will involve building systems that surface patterns across iCloud storage, subscription, engagement, and commerce data — ensuring consistent, accurate reporting across the organization.
• Over time, you will help shape how iCloud data is structured, governed, and delivered, improving the quality, coverage, and efficiency of our analytical data ecosystem.

Minimum Qualifications

• 5+ years of experience in data engineering or business intelligence roles, with demonstrated expertise building and maintaining complex data pipelines and data models at scale
• Strong proficiency with SQL and proven experience querying, manipulating, and analyzing internet-scale data structures and very large datasets
• Advanced proficiency with Python or similar languages, and experience with distributed computing frameworks (e.g., Spark) for complex data manipulation and analytics
• Demonstrated experience with data engineering tools and concepts, including pipeline development, data model design, and aggregation strategies in support of analytics and reporting
• Exceptional written and verbal communication skills, with the ability to translate complex data concepts for diverse audiences including product, business, and engineering stakeholders
• Strong time management skills with the ability to balance multiple projects with competing priorities
• BS in Computer Science, Statistics, Mathematics, Information Systems, Engineering, Economics, or a related field

Preferred Qualifications

• Experience in a fast-paced technology company, digital subscription business, or e-commerce platform, navigating complex data ecosystems
• Familiarity with data governance, data quality frameworks, or metadata management concepts
• MS in Computer Science, Statistics, Mathematics, Information Systems, Engineering, Economics, or a related field

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
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Apple accepts applications to this posting on an ongoing basis.