Software Engineer - Analytics & Data Engineering

Apple; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

Apple in London is seeking a world-class Software Engineer for the ASE Analytics & Data Engineering team. You will build large-scale data pipelines and real-time streaming systems powering App Store, iCloud, Apple Music, Apple TV+, Apple Arcade and more.

You'll collaborate with cross-functional teams across Apple to deliver reliable, scalable data platforms and insights for product and business decisions. You will focus on quality, testing and maintainable code to handle billions of data points

Qualifications

• Several years of experience designing and developing distributed systems.
• Proficiency in Java or Scala for big data processing.
• Experience with modern data processing, streaming and warehousing technologies: Flink (or equivalent) Kafka (or equivalent) Iceberg (or equivalent).

Responsibilities

• Collaborate with partner teams to deliver data engineering solutions.
• Build insights, metrics and data pipelines to power Apple features.
• Work on cross-functional projects with other engineering teams, product leads and analytics leaders.

Skills

Distributed systems

Java

Scala

Big data processing

Flink

Kafka

Iceberg

Education

Bachelor’s or Master’s degree in Computer Science, Software Engineering or equivalent experience

Tools

Spark

Airflow

Job description

Summary

The role is in Apple Services Engineering (ASE) in London. ASE is the team behind high-profile services such as the App Store, Apple iCloud, Apple Music, Apple TV+, Apple Arcade and more. Our Analytics and Data Engineering team is looking for a world-class Software Engineer to develop large-scale systems that will power the next generation of ASE data products.Do you love crafting elegant solutions to distributed problems with billions of data points per day? Are you able to manage the complexity and focus on delivering reliable, scalable solutions for our customers? Join this team, and you will collaborate with engineers across Apple to build and deploy data pipelines and realtime streaming applications that power services and make quick business decisions possible.

Description

The ASE Analytics & Data Engineering team is responsible for building analytics platforms, datasets and processes required by Apple for analysing and powering customer experiences. This means we build computation platforms and datasets to empower our product, marketing, feature, analytic and data science teams. Given the size and complexity of our datasets, this is not a trivial task. We are looking for an outstanding Software Engineer who can effectively collaborate with our partner teams to deliver data engineering solutions to improve and power the next generation of Apple features.You will be working on cross-functional projects with other engineering teams, product leads and analytics leaders to build insights, metrics and data pipelines. You will have the freedom to innovate and have impact as you work closely with our partners to drive meaningful change and build elegant systems to deliver the results.The ideal candidate will have a strong focus on quality and craftsmanship and is motivated by developing reliable distributed systems at scale. Reasoning about complex failure modes and attention to detail with the perseverance to deliver high-quality, well tested and maintainable code, is a must.

Minimum Qualifications

• Several years of experience designing and developing distributed systems
• Proficiency in Java or Scala for big data processing
• Experience with modern data processing, streaming and warehousing technologies: Flink (or equivalent) Kafka (or equivalent) Iceberg (or equivalent)

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering or equivalent experience
• Excellent written and verbal communication skills for collaborating across distributed teams
• Practical experience of maintaining large-scale data pipelines: Spark (or equivalent) Airflow (or equivalent)
• Contributions to open-source tools in the area of data processing
• Strong background in software testing methodologies and practices