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Consumer Electronics, Software, Services, Retail

Software Development Engineer, System Analytics & Intelligence (SAIL)

Cupertino, CAOnsiteFull TimePosted 2 months agoVisa sponsorship available

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Required skills

  • Python
  • backend services
  • APIs
  • system design
  • architecture
  • data pipelines
  • SQL
  • data warehouses
  • data lakes
  • CI/CD

Nice to have

  • Snowflake
  • S3
  • Docker
  • Kubernetes
  • Airflow
  • Spark

Role summary

Core OS is seeking a Software Development Engineer for the System Analytics & Intelligence (SAIL) team. This role focuses on building the data pipelines, services, and platforms that transform workflow data into strategic intelligence to improve developer productivity and software quality. The engineer will own the backend and data infrastructure, designing and building scalable data pipelines and accessible APIs. Strong fundamentals in system design, data handling at scale, and production practices are essential. Experience with cloud data platforms, containerization, and orchestration tools is preferred.

Core OS ships the foundational software that powers every Apple product. At that scale, accelerating developer productivity, elevating software quality, and shaping where the organization invests next take more than intuition - it takes turning massive amounts of workflow data into clear, strategic intelligence. The System Analytics & Intelligence (SAIL) team exists to do exactly that: identify what matters most, drive meaningful improvements to the developer experience, and enable Core OS to ship innovative software with high velocity and high confidence. We're looking for a software engineer who is excited to build the systems that make this possible - the data pipelines, services, and platforms that turn raw signals from across the development lifecycle into insights that drive real organizational decisions.

Description


In this role you will be a hands-on engineer who owns the backend and data infrastructure behind SAIL's analytics products. You'll design and build large-scale data pipelines and the services and APIs that make their output accessible across the organization - from reliable, scalable ingestion and transformation to the interfaces stakeholders actually use. We're looking for engineers with strong fundamentals who enjoy working with data at scale - people who design well-architected systems and care about correctness, reliability, and maintainability. You'll partner closely with teams across Core OS to make sure what you build delivers real impact.

Minimum Qualifications


3+ years building production software systems - including backend services and APIs - with strong proficiency in Python Strong software engineering fundamentals, with demonstrated ability in system design and architecture Hands-on experience building and operating data pipelines, with strong SQL and experience across modern data platforms (data warehouses, data lakes, or similar) Experience with CI/CD and production deployment practices Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience

Preferred Qualifications


Experience working with cloud data platforms (Snowflake, S3, or similar) Experience with containerization technologies such as Docker and Kubernetes Experience with data pipeline orchestration tools (Airflow, Spark, or similar) and transformation frameworks (e.g. dbt) Familiarity with TypeScript/JavaScript or modern frontend frameworks Background in developer productivity, CI/CD systems, or software development workflow domains Experience with BI/visualization platforms such as Tableau

Sample Apple interview questions

  • 1

    Design a typeahead box for a search engine

    system designmedium
  • 2

    Design a rate limiter

    system designmedium
  • 3

    Architect a key-value store for distributed systems.

    system designmedium
  • 4

    Design a system to schedule jobs in a distributed environment

    system designmedium
  • 5

    What is an API and how does it work?

    technicalmedium

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