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In office (Shanghai)
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Senior · 10+ years exp
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Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 9, 2026. Apple scores A on the Alion truth index.

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Apple is an American multinational technology company founded in 1976 by Steve Jobs, Steve Wozniak and Ronald Wayne, and headquartered in Cupertino, California. It designs and sells consumer hardware including the iPhone, Mac, iPad, Apple Watch, AirPods and Vision Pro, together with the operating systems and silicon that run them. A growing services division built around the App Store, iCloud, Apple Music, Apple TV+ and Apple Pay now contributes a large share of profit, making Apple one of the most valuable companies in the world.

Imagine what you could do here. At Apple, new ideas become extraordinary products, services and customer experiences very quickly. Bring passion and dedication to your job and there is no telling what you can accomplish.

The Core Data & Intelligence organization builds the data, models and services that accelerate the growth of Apple's services. We are looking for a Senior Engineering Manager based in Shanghai, China to lead data engineering and quality efforts spanning Apple Services Engineering. You will build and lead a high-performing engineering team comprising data and quality engineers, set the technical direction for large-scale data foundations, services, and automated validation platforms, and partner with cross-functional leaders to turn business needs into scalable, high-quality, privacy-first solutions.

Description

As a Senior Engineering Manager within Apple Services Engineering, you will direct an integrated engineering team responsible for the design, development, quality assurance and operation of massive-scale data pipelines and services across multiple lines of business. Your team's work will support customer-facing features, internal reporting and analytics, and external partner integrations, all held to Apple's exacting standards for reliability, data integrity and privacy.

You will drive both software delivery and quality engineering, championing automated testing, continuous verification, and robust data reconciliation across the entire data lifecycle. You will work across Apple's engineering and business groups, influence platform and quality strategy at the executive level, and build a culture where engineers grow their expertise and impact. This is a hands-on leadership role that demands deep technical judgment, operational rigor, and the ability to recruit, develop and retain top engineering and QA talent in Shanghai.

Minimum Qualifications

10+ years of software or data engineering experience, including 3+ years leading engineering teams with multi-functional scope managing data engineers, software engineers, or QA engineers.

Deep architectural expertise in large-scale data systems, distributed backend services, and software engineering best practices.

Proven track record in data quality engineering, establishing test automation frameworks, CI/CD pipelines, and validation or reconciliation strategies for complex data workflows.

Strong ability to move between hands-on technical depth (code, architecture, test harnesses) and high-level strategy with equal fluency.

Solid grasp of the full data lifecycle, including lineage, governance, data integrity, privacy, retention, and anonymity.

Experience managing cross-functional or hybrid teams of developers and QA or SDET in a global, multi-time-zone environment.

Experience planning and executing large-scale platform modernization, architecture refactoring, or migration programs.

Track record of recruiting, developing, and retaining diverse engineering talent and building high-performing team cultures.

Strong cross-functional collaboration and communication skills, with the ability to influence technical direction and alignment across diverse organizations without direct authority.

Bachelor's degree in Computer Science, Engineering, or equivalent work experience.

Preferred Qualifications

Hands-on experience with large-scale data processing and streaming technologies such as Spark, Flink, Kafka, Apache Iceberg, and Snowflake.

Familiarity with modern data testing and observability frameworks.

Background in AI and machine learning applications within data engineering contexts, such as feature pipelines, model evaluation, or intelligent agent workflows.

Experience operating data platforms at consumer-internet scale, balancing high throughput, low latency, data quality, and privacy.

Domain background in Commerce, Payments, Digital Content, or Subscriptions.

Familiarity with Apple's privacy principles or experience designing privacy-by-default, zero-trust data architectures.

Proven experience hiring and scaling high-caliber engineering teams in the China market.

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