Apple Data Platform team powers analytics and machine learning across Apple. Our mission is to deliver cutting-edge, reliable, and user-friendly infrastructure for data ingestion, storage, processing, and interaction, enabling teams to build data-intensive applications with ease and success. This role sits within the Data Lakehouse team, a part of the Apple Data Platform. The team provides a fully managed Lakehouse solution powered by Apache Iceberg, Iceberg REST Catalog, and custom-built services to manage data at scale. Our platform supports both analytical and machine learning workloads across Apple, serving key products and organizations including Siri, Search, Media, iCloud, News, Apple Intelligence, and Maps. We continuously innovate to meet evolving customer needs and market trends. In this role, you will lead the data lakehouse team, guiding team members in both technical and professional growth. You will collaborate closely with cross-functional teams to lead the planning, execution, and success of technical projects, with a focus on enhancing the experience for Apple’s internal customers.
Description
Apple is seeking a highly motivated and experienced Senior Engineering Manager to lead a team responsible for building and operating our managed Lakehouse platform. The role requires a good understanding of Lakehouse principles, with emphasis on Apache Spark, Iceberg, REST Catalog, along with experience in storage and compute architectures, metadata management, and scalable data processing frameworks to ensure high performance, reliability, and governance at scale.
This role is critical to enabling data-driven decision-making across Apple, powering a wide range of applications from product analytics and machine learning to supply chain optimization and fraud detection. You will be responsible for building and leading a team of talented engineers, driving technical strategy, and ensuring the scalability, reliability, and performance of our data processing infrastructure. You will work closely with data scientists, data engineers, and product teams to understand their needs and deliver innovative solutions around Lakehouse.
Minimum Qualifications
8+ years of software development experience, with a focus on batch and streaming data processing at scale.
4+ years of engineering people management experience; leading, mentoring, and growing teams.
Good understanding of open source data processing frameworks like Apache Spark, Apache Flink, Apache Iceberg, and REST Catalog to operate Lakehouse
Excellent communication, interpersonal, and leadership skills.
Strong problem-solving and analytical skills.
BS, MS, or Ph.D. in Computer Science or a related field of study.
Preferred Qualifications
Proven expertise in operating large Lakehouse leveraging Spark, Iceberg, REST Catalog
Experience building and growing teams focussed on Lakehouse concepts.
Responsibilities
Planning and Execution: Define and drive the technical roadmap for our Lakehouse, ensuring alignment with Apple’s overall data strategy and advancing the adoption of open formats and governance standards; Drive innovation in data processing techniques by exploring emerging technologies and approaches to enhance performance, scalability, and efficiency across the Lakehouse architecture; Lead the design, development, and deployment of robust, scalable Lakehouse leveraging Apache Spark, Apache Iceberg, and the REST Catalog for metadata management and interoperability; Ensure the reliability, availability, and security of the Lakehouse infrastructure to support both analytical and operational workloads; Collaborate with other engineering teams to integrate our data processing technologies with other Apple systems and services.
Team Leadership: Build, mentor, and manage a high-performing team of software engineers with focus on Lakehouse, and related technologies; Foster a culture of collaboration, innovation, and continuous improvement; Provide technical guidance and mentorship to team members, promoting their professional growth; Conduct performance reviews, provide feedback, and identify opportunities for training and development; Manage team workload, prioritize projects, and ensure timely delivery of high-quality solutions.
Stakeholder Management: Partner with data scientists, data engineers, product managers, and other stakeholders to understand their data processing needs and requirements; Communicate technical concepts and solutions effectively to both technical and non-technical audiences; Advocate for best practices in data processing and engineering; Manage expectations and ensure alignment across different teams.
Engineering Thought Leadership: Represent Apple data platform work at external conferences; Deliver presentations, and write blog posts highlighting Apple’s leadership in big data processing.
Eeo Content
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
