Software Engineering Manager, Apple Streaming Platform and Solutions

Summary

Imagine what you could do here. At Apple, new ideas become great products, services, and customer experiences quickly. Bring focus, rigor, and curiosity to your work and help shape the future of Apple’s data infrastructure.

Apple is seeking an experienced software engineer to join the Data Solutions team within Data Services, responsible for building and evolving the distributed data systems that power Apple’s most critical consumer services - including Apple Music, TV, and Podcasts.

You’ll work on high-scale streaming and data processing platforms, solving hard problems around cross-datacenter replication and getting user data to the edge as fast as possible. Your work will directly impact hundreds of millions of Apple users and the teams that build experiences for them.

About the role

Apple’s Streaming Platform and Solutions engineering team, within the broader ASE Data Services organization, builds and operates data infrastructure that is reliable, scalable, and low-latency. The team focuses on real-time data streaming, large-scale data processing, and optimizing cross-datacenter replication to bring user data to the edge with the smallest possible latency.

Apache Kafka plays a central role in our streaming and replication infrastructure, and familiarity with its ecosystem is a meaningful advantage. As a leader, you will manage, mentor, and grow engineers responsible for both internal platform needs and upstream open-source contributions. You will oversee technical execution, maintain engineering standards, and ensure operational excellence across the Kafka ecosystem.

Responsibilities

Team Leadership & Mentorship: Actively lead, mentor, and grow a team of software engineers. Guide technical skill development, conduct design and code reviews, and foster a culture of technical rigor, continuous learning, and inclusivity.

Hands-On Technical Strategy & Coding: Stay directly involved in technical execution by writing code, reviewing pull requests, evaluating architectural trade-offs, and driving best practices for performance, scalability, data consistency, and fault tolerance in distributed platforms.

• Cross-Regional Alignment: Partner closely with distributed leadership and cross-functional teams across regions to translate business objectives into technical execution, unblock dependencies, and align team roadmaps with global initiatives.
• Operational Excellence & Delivery: Directly participate in architectural reviews, incident management, and performance tuning to ensure high availability, low latency, and operational stability for platform services operating at global scale.
• Team Growth & Execution: Provide hands-on technical guidance to help engineers navigate complex projects, accelerate their career growth, and maintain a high standard of engineering execution while supporting a healthy work-life balance.

Minimum Qualifications

• 5+ years of experience in software development, with at least 3 years in distributed systems or messaging platforms at scale.
• 2+ years of technical leadership experience overseeing complex projects and multiple engineers.
• Proven track record of building and leading infrastructure teams with credibility and influence.
• Proficiency in Java, Scala, or other languages used in Kafka development.
• Advanced understanding of algorithms, data structures, fault tolerance, and performance for large-scale messaging systems.
• BS, MS, or PhD in Computer Science or a related technical field, or equivalent practical experience.

Preferred Qualifications

• Deep knowledge of Kafka broker internals, replication, partitioning, client libraries, and event delivery guarantees.
• Familiarity with distributed systems concepts such as consensus protocols, consistency models, and fault tolerance.
• Experience with multi-datacenter deployments, load balancing, quota management, and tenant isolation.
• Strong background in testing methodologies, including fault injection, property-based testing, and performance benchmarking.
• Ability to drive operational excellence, including monitoring, incident response, and long-term remediation strategies.
• Experience contributing to open-source projects, ideally Apache Kafka or related ecosystems.
• Hands-on expertise with Apache Kafka internals and distributed system design.