About this role
Do you enjoy crafting elegant solutions to distributed problems with billions of data points per day? Can you manage business complexity and still deliver reliable, scalable systems? If so, join us! You will work with engineers across Apple to build data pipelines and real-time streaming applications that power Apple Music, Shazam, Apple Podcasts and Fitness+ services.
We build big-data and real-time data platform components and pipelines. We are domain experts who work alongside product, business and client engineering teams. AI is already a core part of how we work. We have access to leading frontier tools and use agentic engineering to accelerate our development, operations and support work. Our data supports a modern AI stack powering features and recommendations.
Minimum Qualifications
Substantial experience designing, building and operating business-critical, large-scale distributed systems.
Fluency in at least one statically typed language, ideally Java or Scala, and a strong grasp of big-data fundamentals: concurrency, memory management, networking and performance optimisation.
In-depth understanding of at least one distributed or big-data system, such as Kafka, Flink, Spark, Trino, Iceberg or Cassandra.
Experience gathering requirements and turning ambiguous business needs into clear, accurate technical specifications.
A focus on quality and craftsmanship: You reason well about complex failure modes and deliver well-tested, maintainable code.
Preferred Qualifications
Practical experience maintaining large-scale data pipelines with Spark and Flink.
Experience with cloud, container and infrastructure tools such as Kubernetes and Docker.
Effective use of AI tools such as Claude in day-to-day engineering.
Contributions to open-source data-processing projects.
Excellent written and verbal communication across distributed teams.
Bachelor's or Master's degree in Computer Science, Software Engineering or equivalent experience.