Job Description

Locations

• Cupertino, California, United States 95014

Salary

Skills Required

• leadershipintermediate
• team managementintermediate
• technical guidanceintermediate
• professional developmentintermediate
• collaborationintermediate
• cross-functional teamworkintermediate
• project planningintermediate
• project executionintermediate
• Lakehouse principlesintermediate
• Apache Sparkintermediate
• Apache Icebergintermediate
• Iceberg REST Catalogintermediate
• storage architecturesintermediate
• compute architecturesintermediate
• metadata managementintermediate
• scalable data processing frameworksintermediate
• data ingestionintermediate
• data storageintermediate
• data processingintermediate
• analyticsintermediate
• machine learningintermediate
• technical strategyintermediate
• scalabilityintermediate
• reliabilityintermediate
• performance optimizationintermediate
• governanceintermediate
• data-driven decision-makingintermediate

Required Qualifications

• 8+ years of software development experience, with a focus on batch and streaming data processing at scale. (experience, 8 years)
• 4+ years of engineering people management experience; leading, mentoring, and growing teams. (experience, 4 years)
• Good understanding of open source data processing frameworks like Apache Spark, Apache Flink, Apache Iceberg, and REST Catalog to operate Lakehouse (experience)
• Excellent communication, interpersonal, and leadership skills. (experience)
• Strong problem-solving and analytical skills. (experience)
• BS, MS, or Ph.D. in Computer Science or a related field of study. (experience)

Preferred Qualifications

• Proven expertise in operating large Lakehouse leveraging Spark, Iceberg, REST Catalog (experience)
• Experience building and growing teams focussed on Lakehouse concepts. (experience)

Responsibilities

• 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.
• 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.

Tags & Categories