Job 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. 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 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

Requirements

Must-haves

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
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)

Nice-to-haves

Experience building distributed, high-volume data services is a plus

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

javapythonsqlaws

Platform: apple
Effort: medium