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Senior Product Data Engineer

Apple

Salary not specified
Sep 5, 2025
Austin, TX, US
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Apple Services Data Science & Analytics team drives decisions that improve the customer experience, accelerate growth, and uncover new business opportunities, all while respecting user privacy. The Data Engineering team within Services Data Science & Analytics focuses on solving the challenges inherent in producing consistent and reliable analytics from massive datasets across a wide range of services.

Requirements

  • 5+ years of experience as a Data Engineer or similar role
  • 5+ years of experience with data schema design and data modeling
  • 5+ years of experience in Python and SQL
  • 2+ years of Spark/PySpark experience
  • Business Intelligence experience - aggregated data sources, metric definition, data visualization with tools like Tableau
  • Deep experience in Spark
  • Experience with container orchestration and deployment frameworks (eg. Kubernetes, Docker)

Responsibilities

  • Independently design technical solutions to process massive datasets (billions of daily records) and unify analytics across Apple Services
  • Build data pipelines using Python, PySpark and SQL
  • Manage an evolving data schema ensuring that data structures can extend over time while also maintaining backward compatibility
  • Collaborate with Business Intelligence and Data Science teams to design aggregate tables used across multiple teams and workflows
  • Integrate new tools and packages into the team’s workflow and codebase
  • Provide on-call support and monitoring
  • Mentor and provide data engineering best practices across the organization

Other

  • Bachelors degree in Computer Science, Statistics, Mathematics, Engineering, Information Systems, Economics or related field
  • Experience in digital subscriptions, media, and/or app-based engagement data
  • Experience in Data Governance & User Privacy
  • Data Platform engineering experience to support deployment of pipelines across many diverse teams
  • Masters degree in Computer Science, Statistics, Mathematics, Engineering, Information Systems, Economics or related field