Engineering Manager, App Insights, Services Data Science & Analytics
Apple Cupertino, California, United States
Computers and Electronics Manufacturing · 10,001+ employees
About the role
Lead a team of engineers to deliver reliable, scalable data products and analytical solutions for strategic business services. Collaborate with cross-functional stakeholders across legal, product, and business teams to translate complex data requirements into actionable insights.
What they look for
Requirements
Requires 8+ years of experience in data engineering or analytics with at least 3 years in a management role. Candidates must possess a strong technical foundation in SQL, data modeling, and experience supporting regulatory or compliance-adjacent workflows.
Full description
Are you ready to lead a high-performing team of engineers and data practitioners at the intersection of analytics, data engineering, and business intelligence within Apple? If you are passionate about building teams that deliver reliable, scalable, and impactful data products — and thrive in environments that demand both technical depth and executive-level stakeholder partnership — we would love for you to apply!
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. 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.
Description
As the Engineering Manager of App Insights, you will lead a team of engineers responsible for the full analytics and data engineering stack supporting some of Apple's most strategic and high-visibility services businesses.
Your team's scope spans business intelligence, self-service reporting, ad hoc analysis, data engineering, and regulatory and legal data support — delivering the analytical foundation that business, product, legal, and executive stakeholders rely on daily.
A great fit for this role is a technically grounded manager who leads with clarity and composure, builds trust across a wide range of stakeholders, and raises the bar for the engineers they develop. You will set direction, own delivery, and be accountable for the quality, reliability, and business impact of your team's output.
You will collaborate closely with cross-functional leaders across legal, compliance, product, and business teams — translating complex and often time-sensitive data requirements into well-executed analytical solutions.
Over time, you will help define the technical and operational roadmap for App Insights, advocate for your team's needs, and play a key role in shaping DS&A's overall approach to data quality, governance, and self-service analytics.
Minimum Qualifications
8+ years of experience in data engineering, analytics engineering, or business intelligence, with at least 3 years in a people management role Demonstrated ability to lead and develop a team of engineers — including hiring, performance management, and career development Strong technical foundation in SQL, data pipeline development, and data modeling at scale Experience supporting legal, regulatory, or compliance-adjacent analytics workflows, with an understanding of the sensitivity and precision required Proven stakeholder management skills — comfortable operating at multiple levels of an organization, from hands-on technical teams to senior business and legal leadership Strong written and verbal communication skills with the ability to synthesize complex data topics into clear executive-level narratives BS in Computer Science, Statistics, Engineering, Mathematics, Information Systems, or a related field
Preferred Qualifications
Experience managing teams in a fast-paced technology company or large-scale digital services business, with exposure to subscription, commerce, or app platform data ecosystems Proficiency with Python or similar scripting languages, and familiarity with distributed computing frameworks (e.g., Spark) for large-scale data processing Experience building or overseeing self-service BI tooling or analytics platforms used by non-technical stakeholders Familiarity with data governance, data quality practices, or regulatory data production workflows MS in Computer Science, Statistics, Engineering, Mathematics, Information Systems, or a related field
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