Requirements

Substantial experience designing, building and operating business-critical, large-scale distributed systems.
Fluency in at least one statically typed language, ideally Java or Scala.
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 translating ambiguous business needs into clear technical specifications.
Focus on quality and craftsmanship, including reasoning about complex failure modes and delivering well-tested, maintainable code.

Nice to Haves

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 daily engineering tasks.
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.

Building data pipelines and real-time streaming applications powering Apple Music, Shazam, Apple Podcasts and Fitness+ services.
Developing big-data and real-time data platform components and pipelines.
Collaborating with product, business and client engineering teams as domain experts.
Integrating AI as a core part of development, operations and support processes.
Supporting a modern AI stack that powers features and recommendations.