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Apple Media Products (AMP) - Software Data Engineer - Machine Learning

Location:
London
Company:
Apple

Description

Apple is looking for a strong Software Data Engineer with Machine Learning experience for our Apple Media Products (AMP) division to build and maintain highly scalable data pipelines and systems. The role involves building and engineering large scale, robust and resilient big data pipelines. AMP is responsible for services including App Store, Apple Music, Apple TV+, Podcasts, and Book Store. Our services reach hundreds of millions of customers around the globe, and have revolutionized how we interact with digital media. Our Engineering team is looking for hardworking, performance-savvy, engineers to build out the big data platform and services which power many of these customer features — existing and new.
Key qualifications:
Experience with pipelines and architectures that support deployment of machine learning algorithms and production applications Proven understanding and experience in data warehousing, data modelling and data structures. Experience implementing and supporting highly scalable data systems and services. Prior experience working with big data technologies and distributed systems (e.g. Hadoop, Spark) Proficiency working in Scala, Java, SQL and Python Experience with streaming technologies including Kafka, Kinesis a plus Knowledge of PIIs and GDPR compliance to meet privacy standards a plus
This is your opportunity to help engineer highly visible global-scale systems with petabytes of data, supporting hundreds of millions of users. Successful candidates will have strong engineering and communication skills, as well as, a belief that data driven processes lead to phenomenal products. You will need to have a real passion for quality and an ability to understand complex systems. This role includes elements both of ad hoc analysis as well as roll up of production grade data feeds. This role also includes an essential thread of data privacy and security. This is a rare opportunity to join a focused team and work collaboratively with other groups to make a significant impact
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