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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.
DESCRIPTION
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.