Engineering Manager, App Store Data
Apple
Software Engineering, Other Engineering
San Francisco, CA, USA
USD 228,100-342,800 / year + Equity
Posted on May 2, 2026
Apple’s App Store is the world’s largest and most innovative app marketplace, home to over 1.5 million apps and serving more than half a billion customers every week across all the Apple devices. Since the App Store launched in 2008, it has changed how we all live; it has enabled countless new companies, spawned new industries, and built millions of jobs. But we believe we are just getting started. Do you have a strong passion for using data to drive business decisions, generate ideas, and inspire collaborators? If so, join us, you will play an integral role in helping App Store make decisions using data and improve the store every day for both users and developers by generating analysis from data in a privacy-friendly manner. We enable data-driven innovation by building solutions, services, and analytics for a variety of internal stakeholders and external partners. In a world where apps have become essential in people’s daily lives, the App Store team has become essential to Apple’s business.
We are seeking an Engineering Manager to lead App Store’s growing data engineering and analytics function. This team owns compliance critical data products and the EM is accountable not just for delivery, but for the correctness and team adherence to compliance controls, reviewer of design decisions with privacy/legal implications. 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. As a technical manager, you’ll 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.
- 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 and enforce standards for metrics, data governance, documentation, and SLAs, overseeing data quality with proactive issue resolution through alerting and root-cause analysis
- Build, coach, and elevate a high-performing analytics engineering team, setting clear goals and fostering a culture of inclusion, learning, and operational excellence
- Collaborate closely with product and engineering to prioritize the analytics engineering roadmap and drive data-driven decision-making
- Scale data self-service and literacy by expanding documentation, training, and enablement in key tools and dashboards, empowering stakeholders to explore data independently
- Guide architectural and operational excellence across data pipelines, championing best practices in code review and version control for enhanced reliability
- Build in-person relationships with team members and contribute to Apple’s company culture
- 10+ years in analytics engineering, data engineering, or analytics, with strong hands‑on SQL, Python or Java, Scala and data modeling expertise
- 3+ years of people leadership experience, including hiring, coaching, and performance management in analytics/data teams
- Proven ability to define semantic layers and build scalable dashboards; experience with Trino, Superset or other BI/visualization tools.
- Experience building and operating data pipelines with robust validation and monitoring; high bar for data quality
- Excellent communication; proven success partnering with cross‑functional stakeholders (Product, Engineering, Legal, Privacy etc.) to define KPIs and deliver measurable outcomes
- Track record of driving projects end‑to‑end and demonstrating clear outcomes and impact
- Appetite for applying AI and emerging tools to increase productivity and reimagine how DE teams deliver impact (without sacrificing rigor and decision quality)
- Experience with Regulatory and Compliance engineering - GDPR operational requirements, data minimization, DMA, DSA obligations, Privacy-first data architecture at a technical level.
- Experience working with privacy, legal and regulatory stakeholders in an engineering capacity