Software Engineer - Power and Performance Analytics Platform

About this role

The Core Telemetry Platform team is responsible for building state-of-the-art platforms and tools to support the complete lifecycle of data, from creation to analytics and insight discovery. A key component of this is our Analytics Platform team, which focuses on developing client-facing analytics tools & technologies. This team is seeking a motivated and passionate engineer to spearhead the advancement of its portfolio: comprehensive dashboards, automated pipelines to monitor hundreds of metrics, and innovative AI-based analytics solutions. Are you excited about creating out-of-the-box solutions? Are you interested in doing the best work of your live? If this describes you, we would love to hear from you!

Description We're looking for a motivated engineer with excellent programming, problem solving and communication skills. As a member of this team, you will have the opportunity to solve challenging engineering problems across a broad range of Apple products. You will be responsible for understanding the challenges faced by any team looking to do large-scale analytics, and designing and building systems to address those challenges. You will enable continued innovation and progress within the analytics platform through research and development. You will help and support the execution, test and roll-out of solutions. To be successful in this role, you must have a solid software engineering background and be able to write production level code.

Minimum Qualifications B.A. or B.S. in Computer Science or equivalent field 2 years of programming experience in Python, Java, Swift, or C++ Experience designing and developing production-level software Self-motivated and able to work independently

Preferred Qualifications M.S. in Computer Science or equivalent field Strong analytical thinking Excellent spoken and written communication skills Experience driving cross-functional projects with diverse sets of stakeholders Proficiency with distributed compute & storage technologies (e.g., Spark, Flink, HDFS) Proficiency using AI to build analytics workflows