Senior Software Engineer

Apple Inc.; Greater London; On-site; GBP 120,000 - 190,000; Full time

Job summary

Apple Inc. in London is seeking an experienced data systems engineer to design, build and operate large-scale distributed pipelines and real-time streaming applications powering Apple Music, Shazam, Apple Podcasts and Fitness+ services.

You will collaborate with product, data science and analytics teams to translate complex requirements into robust datasets, metrics and insights, while driving technical direction and ensuring reliability across high-throughput systems.

Qualifications

• Experience designing, building and operating large-scale distributed systems.
• Fluency in Java or Scala and a strong grasp of big-data fundamentals.
• Experience with Kafka, Flink, Spark, Trino, Iceberg or Cassandra.
• Experience gathering requirements and turning ambiguous business needs into clear technical specifications.
• Focus on quality and craftsmanship: write well-tested, maintainable code.

Responsibilities

• Design, build and evolve distributed compute frameworks, data pipelines and real-time streaming applications that process billions of data points per day.
• Turn questions into specs: translate partner needs into clear datasets, metrics and requirements.
• Deliver on cross-functional projects with engineering, product, data science and analytics teams to build datasets, metrics and insights.
• Drive technical direction from discovery to production, balancing cost, complexity and performance.
• Run production systems with on-call responsibilities and harden systems against failures.
• Mentor engineers and champion testing and engineering best practices.

Skills

Distributed systems

Java/Scala

Big data

Requirements gathering

Code quality/testing

Education

Bachelor's or Master's in CS/SE

Tools

Kafka

Flink

Spark

Trino

Iceberg

Cassandra

Kubernetes

Docker

Job description

London, England, United Kingdom Software and Services

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.

Responsibilities

• Build at scale: Design, build and evolve distributed compute frameworks, data pipelines and real-time streaming applications that process billions of data points per day.
• Turn questions into specs: Work with partners to understand what they need and why. Write clear technical specs that define datasets, metrics and requirements, and review specs written by others.
• Deliver with partners: Work on cross-functional projects with engineering teams, product leads, data scientists and analytics leaders to build datasets, metrics and insights.
• Drive technical direction: Lead initiatives from problem discovery through to production. Weigh cost, complexity and performance, and choose the right tool for each problem.
• Run it well: Share ownership of high-throughput, low-latency production systems. That includes on-call, and hardening systems against failure before it happens.
• Raise the bar: Do thorough code and design reviews, mentor other engineers, and champion testing and engineering best practices.

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.

At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. As a registered Disability Confident employer, we will work with applicants to make any reasonable accommodations. Apple will consider for employment all qualified applicants with criminal backgrounds in a manner consistent with applicable law. Learn more

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