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Apple · Seattle, WA
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. Description 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 pe