Engineering Manager, App Store Data
Apple - San Francisco, United States of America
Posted May 1, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
- Not verified last checked Jun 13, 2026
- Salary
- Not verified not verified - source not recorded; timestamp not recorded
- 401(k) match
- Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.
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Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Engineering Manager, App Store Data San Francisco, United States of America Apple's App Store serves half a billion customers every week across every Apple device, and has fundamentally changed how people discover, access, and build software since 2008. It is central to Apple's business and to the global developer ecosystem. Building and leading the data team behind it means operating at a level of scale, accountability, and organizational influence that few engineering leaders encounter. We are seeking an Engineering Manager to lead App Store's data engineering and analytics team. This team owns compliance-critical data products: pipelines and analytical outputs subject to regulatory and privacy obligations, as well as analytics engineering, EDA, ML-based pipeline health monitoring, and self-serve data products. The EM is accountable not just for delivery, but for the correctness of compliance data products and team adherence to compliance controls. This role blends technical depth with people leadership - you'll lead with empathy and energy, guide engineering execution, ensure operational excellence, and stay hands-on in key parts of our data ecosystem. You will partner closely with stakeholders across the App Store business to translate strategic priorities into scalable data solutions, sustainable delivery practices, and a strong culture of ownership and growth. AI-native development is a standard operating mode with EM expected to model and champion AI-native engineering practices across the full SDLC. Develop and own the vision for Analytics Engineering, delivering curated datasets, dashboards, and internal data products. Define outcomes and communicate prioritization, progress, and impact to leadership Establish
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