Senior Engineering Manager, Core Data & Intelligence
Software Engineering, Other Engineering
Posted on Nov 12, 2026
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.
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.
- Team Leadership and Culture: Build, lead, and mentor an engineering team in Shanghai encompassing data engineers and a dedicated QA engineer. Foster a culture of craftsmanship, technical ownership, and continuous delivery.
- Architecture and Delivery: Direct the end-to-end design, implementation, and production operations of robust, highly scalable data pipelines, platforms, and supporting backend services.
- Hands-on Technical Leadership: Serve as a visible technical contributor, diving deep into architecture, data modeling, test strategies, and complex technical problems alongside the team rather than directing from a distance.
- Quality and Verification Strategy: Champion the end-to-end data quality roadmap. Partner directly with QA and engineering to architect automated regression suites, pipeline validation harnesses, data reconciliation, and anomaly detection systems.
- Cross-Functional Partnership: Partner with engineering, product, and data science teams across Apple to align data and validation capabilities with customer-facing features, business analytics, and partner integrations. Translate business requirements into technical capabilities and roadmaps.
- People Development: Recruit, mentor, and retain top engineering and quality talent, supporting career progression and developing emerging technical leaders within the Shanghai hub.
- Standards and Governance: Establish and uphold engineering standards for data accuracy, pipeline reliability, CI/CD, test coverage, scalability, and Apple's privacy-by-default principles.
- AI and Automation: Guide the team in building and adopting LLM-powered applications, intelligent agents, and automated validation tools at scale to eliminate routine manual verification and boost developer velocity.
- Executive Alignment: Communicate data and quality strategy, program milestones, operational health, and cross-team dependencies clearly to senior leadership and global stakeholders.
- 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.
- 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.