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.

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.