Engineering Manager, App Store Data

Apple Inc

Quick summary

Work type: On-site
Location: San Francisco, CA
Salary: $228,100–$342,800 / yr
Posted: 34 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $195k

This role $285k

$130k most similar roles pay here $366k

This role pays more than 96% of similar roles. Most pay $153,587–$236,900 — the shaded band above. At the midpoint, this role pays about $285k versus about $195k 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 969 open roles on FindRole.

Listed pay typically runs $163,300–$272,100 across 756 roles with salary data.

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At a glance

TL;DR · Engineering Manager, App Store Data

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As an Engineering Manager for Apple's App Store Data team, you will lead a compliance-critical data engineering and analytics team responsible for pipelines and analytical outputs subject to strict regulatory and privacy obligations. Your role involves defining the vision for analytics engineering, ensuring data quality through rigorous standards and proactive issue resolution, and fostering a high-performing culture of operational excellence and ownership. You will work closely with cross-functional stakeholders to prioritize the roadmap and drive data-driven decision-making while scaling self-service capabilities through documentation and training. The team operates at an unprecedented scale, requiring expertise in SQL, Python, Java, Scala, and data modeling, along with hands-on experience in AI-native engineering practices across the full SDLC. This role demands a blend of technical depth and people leadership to ensure compliance and operational excellence in a highly regulated environment.

Skills

Python Java Scala SQL Trino Superset CI/CD LLM-augmented workflows Terraform AWS Kubernetes Git Docker Prometheus Grafana PostgreSQL Snowflake BigQuery AI-native engineering practices

What you'll do

Develop and own the vision for Analytics Engineering, delivering datasets and dashboards to leadership.
Establish standards for metrics, governance, documentation, and SLAs, ensuring proactive issue resolution.
Build and coach a high-performing analytics engineering team, setting goals and fostering operational excellence.
Prioritize the analytics engineering roadmap with product and engineering teams, driving data-driven decision-making.
Scale data self-service by expanding documentation, training, and enablement in key tools and dashboards.
Guide architectural and operational excellence across data pipelines, championing best practices for reliability.
Ensure rigorous review of AI-generated code in compliance-critical contexts.

What we're looking for

7+ years of experience in analytics or data engineering with expertise in SQL, Python, Java, Scala, and data modeling
3+ years of leadership experience in hiring, coaching, and managing performance in analytics/data teams
Proven ability to define semantic layers and build scalable dashboards using tools like Trino and Superset
Experience building and operating robust data pipelines with validation and monitoring for high-quality data outputs
Strong communication skills and success partnering with cross-functional stakeholders to define KPIs and deliver measurable outcomes
Track record of driving projects end-to-end, demonstrating clear outcomes and impact in a compliance-critical context
Active use and promotion of AI-native engineering practices across the software development lifecycle

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