Data Engineering Manager
Santa Clara Valley (Cupertino),California,United States
Software and Services
Track record of building and leading high-performance software engineering teams.
Strong sense of ownership of the development process and the will to drive the team toward constant code, application and process improvements.
Excellent interpersonal skills and ability to collaborate effectively across multiple business and technical teams.
Excellent problem solving, critical thinking, and social skills - Lead by example to empower and challenge the team to deliver their best.
Multiple years of Data Engineering management experience leading and supporting the development and maintenance of applications, tools and processes.
Experiencing architecting, building and maintaining complex, multi-component big data systems.
Shown ability to work under pressure while maintaining a high level of quality and integrity.
Description
Does leading the engineering which ingests, processes, stores and analyzes petabytes of interesting telemetry data excite you? We’re looking for you! Are you an experienced Software Engineering Manager? In this role you’ll both set direction and provide mentorship to our experienced engineers and work hands-on to solve sophisticated problems from the device level all the way to big data scale. You’ll be responsible for the development, quality and integrity of the data pipelines which deliver a diverse set of data types to other engineering teams at apple. In this role you’ll have a large impact on the entire Apple Software Engineering organization and ultimately help Apple improve, build and deliver the products which consistently delight our users.
Education & Experience
B.S. in Computer Science or equivalent experience
Additional Requirements
Expert level experience with Data Engineering tools and frameworks, processes, goals and methodologies.
Expert level experience with at least two of the following languages and related development tools: (Python, Ruby, Java, Scala, Swift, Objective C).
Experience with one or more of the following platforms: HDFS, Yarn, Spark, Impala, Kafka, HBase, MapReduce, Kubernetes, Object Store, Flink.
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