Senior Software Engineer - Distributed Systems

San Diego, CA, US • Posted 1 day ago • Updated 11 hours ago
Full Time
On-site
Fitment

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Job Details

Skills

  • Team Building
  • Data Collection
  • Visualization
  • Interfaces
  • Data Analysis
  • Software Engineering
  • Computer Science
  • Cloud Computing
  • Amazon Web Services
  • Orchestration
  • Kubernetes
  • Amazon EC2
  • Apache Mesos
  • Apache Flink
  • Amazon Kinesis
  • Optimization
  • Writing
  • Apache Parquet
  • Continuous Integration
  • Continuous Delivery
  • Adaptability
  • Communication
  • Critical Thinking

Summary

Are you ready to embrace massive scale? Undaunted ingesting petabytes of raw data each day from more than a billion customer devices? \\n\\nApple's Data Analytics team is looking for a motivated and driven distributed systems engineer to work on our device telemetry platform. We need a talented software developer to join our tight-knit cross-functional engineering team, building services and applications to parse, persist, and understand how Apple customers use their devices.

We collect, analyze, and produce insights from diagnostic and usage data from Apple devices. Our data is used to improve products and services and inform the overall direction of Apple platforms. \n\nOur engineering responsibility spans device, data collection, compute, and query and visualization interfaces. As part of the Data Analytics team, you will similarly work cross-functionally to design, build, and iterate on our stream processing and ingestion pipeline. \n\nCollaborating with data scientists and engineers across Apple, you will capture and refine requirements, validate design decisions, and implement. This role has high visibility and impact within the Apple Software Engineering organization.

BS degree in Computer Science, equivalent field or equivalent work experience\n5+ years SW development experience\nHave worked on large distributed systems, ideally on a public cloud platform like AWS\nExtensive experience with container-based orchestration (Kubernetes, EC2, Mesos, etc.)\nPractical knowledge of queue/stream consumers like Flink or Kinesis\nExposure to profiling and optimization of scale compute and data pipelines\nProficiency writing/maintaining large-scale Iceberg or partitioned Parquet\nUnwavering commitment to CI/CD

Comfortable and adaptable in a dynamic/informal environment with shifting priorities\nExcellent verbal and written communication skills\nSelf-motivated and dedicated with creative and critical thinking capabilities\nBig data query engine production experience (Presto/Trino/Athena, etc.)
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90733111
  • Position Id: b88c80e4f80a7a341e6a52a09b875c4f
  • Posted 1 day ago
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