Software Engineer, Big Data - Apple Services Engineering

Summary

The Apple Services Engineering team is one of the most exciting examples of Apple’s long-held passion for combining art and technology. This team powers the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books, operating at massive scale and meeting Apple’s high standards for performance and quality to deliver entertainment in over 35 languages across more than 150 countries.

We are seeking a Software Engineer to join Apple Services Engineering (ASE) who brings a deep passion for building large-scale distributed data processing systems, frameworks, and platforms using big data technologies.

Description

As a team member of the ASE Analytics & Data Engineering team, you will have significant responsibility and influence in shaping the team’s future direction. This role is inherently cross-functional, and the ideal candidate will work closely across disciplines. We are looking for someone with a strong love for data and the ability to iterate quickly across all stages of the data pipeline lifecycle.

This position involves working on a small, highly collaborative team to develop large-scale data pipelines and analytical solutions using big data technologies. Successful candidates will demonstrate strong engineering and communication skills, along with a belief that data-driven processes lead to exceptional products. You should have a passion for quality and an ability to understand and evolve sophisticated systems.

Preferred Qualifications

Excellent collaboration and communication skills, with the ability to listen, influence, and drive solutions cohesively

Minimum Qualifications

Bachelor’s or Master’s degree in Computer Science, Statistics, a related quantitative field, or equivalent practical experience
6+ years of experience building production systems using Java and/or Scala, with strong proficiency in Java and/or Scala for large-scale distributed data processing and familiarity with functional programming paradigms.
Deep understanding of distributed batch and streaming data processing systems such as Spark, Flink, and Kafka
Experience with big data ecosystem technologies such as HDFS, Hadoop, S3, MPP database, Kubernetes and Airflow.
Proven track record of designing, launching, and scaling production-quality data pipelines that power product features
Strong data intuition, backed by solid SQL and data analysis skills
Experience with GDPR compliance and best practices for collecting, processing, and sharing data responsibly