Would you like to drive the future of Apple’s products, applications, and platform while having the unique opportunity to impact some of the most far-reaching software applications in the world? iCloud Data organization enables Apple to ship better products for iCloud users to access all their content across apps (Photos, Mail, Messages, FaceTime, Calendar etc) from all of their devices all the time by providing consistent, scalable, timely, accurate, complete and fully integrated data infrastructure and capabilities to accurately surface relevant information. If this excites you and you are energized by solving hard, high-leverage problems at scale, we'd love to hear from you! We’re looking for exceptional data engineers who have a strong background in distributed data processing, have great and demonstrable data intuition, and share our passion for continuously improving the ways we use data to make the Apple’s products, applications, and platform better.
Description
What you will do: Engineer efficient, adaptable and scalable data pipelines to process structured and unstructured data Own and evolve extremely rich datasets on iCloud products and platform interactions to power a wide variety of use cases Build forward-looking data solutions that interface well with existing systems and use judgement to bring cutting edge technologies in the industry to suit iCloud needs Understand how key technical decisions will drive business outcomes and deliver/aid data frameworks and platforms that improve delivery with high-quality to those outcomes by partnering with cross functional teams Join a stunning team of data experts with diverse skill set, and deliver excellent solutions that better enable our decision-making process.
Preferred Qualifications
Experience with Cloud Computing platforms like Amazon AWS, Google Cloud
Experience with building stream-processing applications using Apache Flink, Spark-Streaming, Apache Storm, Kafka Streams or others
Experience with Search systems (such as ElasticSearch, Solr), NoSQL datastores (such as HBase, Cassandra, MongoDB)
Experience building distributed, high-volume data services is a plus
Minimum Qualifications
8+ years of experience working with Spark and other distributed data technologies (e.g. Hadoop, Presto, Flink, Druid) for building efficient & large scale data pipelines
Highly proficient in at least one of Java, Python or Scala
Deep expertise in Data Principles, Data Architecture & Data Modeling, Strong SQL skills
Strong problem solver with meticulous attention to detail, capable of taking on loosely defined problems
Experience working in a complex, matrixed organization involving cross-functional, and/or cross-business projects
Strong communication and collaboration skills & ability to lead high-level discussions on technology strategy and approach
Conceptually familiar with AWS cloud resources (S3, EC2, RDS etc)
MS or BS in Computer Science, Engineering, Mathematics, Statistics or a related field OR equivalent practical experience in Software or Data Engineering
