Data Engineer (Java, Spark / Flink) - AMP Commerce Engineering at Apple (Seattle, WA)
The Apple Media Products Engineering team is one of the most exciting examples of Apples long-held passion for combining art and technology. These are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books. And they do it on a massive scale, meeting Apples high expectations with high performance to deliver a huge variety of entertainment in over 35 languages to more than 150 countries.
These engineers build secure, end-to-end solutions. They develop the custom software used to process all the creative work, the tools that providers use to deliver that media, all the server-side systems, and the APIs for many Apple services.
The Commerce Engineering team is looking for an experienced, hardworking and proactive software engineer to lead several data architecture and technical compliance efforts across the commerce landscape. Join our exciting engineering team that has been owning the digital distribution industry by constantly developing innovative features to grow and expand the iTunes Store, App Store, iBooks Store and services such as Apple Music, TV+ and Arcade.
The position requires someone comfortable with all aspects of the software design lifecycle and experienced with high performance data distributed systems. If you thrive in a dynamic multi-functional environment and are able to pivot with constantly evolving requirements and new technologies, youll love it here.
You will be an integral part of the team that is in a unique position to develop and build the commerce data platform. You will participate in the instrumentation and ingestion of events. You will collaborate with partners on data pipelines and datasets and ensure that data is handled in a privacy-safe manner. This platform allows downstream customers to utilize the unified data foundation to achieve consistency, quality, and efficiency. You will have experience to design and implement large scale commerce datasets and backend services. Those data systems will be utilized by many downstream teams for data analysis, metric reporting, data insights, model training and evaluation. You will implement data storage solutions that scale, enrich and surface data quality and pipeline metrics. In addition, you must be able to investigate and adopt new technology, be comfortable working in a fast-paced environment, and have a can-do attitude.
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