SAIL Backend Engineer – Data Pipelines & Analytics

Apple Inc.; Cupertino (CA); On-site; USD 150,000 - 278,000; Full time

Benefits offered by this job

Health benefits

Retirement plan

Employee stock purchase

Relocation assistance

Job summary

Apple Inc. in Cupertino, California, seeks a Software Development Engineer for the System Analytics & Intelligence (SAIL) team. You will design and build backend data pipelines and services that turn raw signals from the development lifecycle into insights used across Core OS.

You will own architecture, reliability, and performance of systems, work with cross‑functional teams, and apply strong Python and data engineering fundamentals to deliver scalable analytics platforms.

Qualifications

• 3+ years building production software systems with strong Python
• Strong software engineering fundamentals with system design
• Hands-on experience building and operating data pipelines with SQL and data platforms
• Experience with CI/CD and production deployment practices
• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience

Responsibilities

• Design, build, and operate large-scale data pipelines and transformation workflows that power Core OS workflow analytics
• Build backend services and APIs that make data insights accessible and actionable across Core OS
• Own architecture, reliability, performance, and extensibility of the systems you build
• Partner with engineering teams to translate analytics needs into scalable technical solutions

Skills

Python

System design

SQL

CI/CD

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Docker

Kubernetes

Airflow

Spark

dbt

Snowflake

S3

Job description

Apple Inc. in Cupertino, California, seeks a Software Development Engineer for the System Analytics & Intelligence (SAIL) team. You will design and build backend data pipelines and services that turn raw signals from the development lifecycle into insights used across Core OS.

You will own architecture, reliability, and performance of systems, work with cross‑functional teams, and apply strong Python and data engineering fundamentals to deliver scalable analytics platforms.