Job Details

Weekly Hours: 40

Role Number: 200621515-0836

Summary

Apple is where individual creativities gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something — you'll add something.

Description

The Siri Quality Engineering team is seeking an Analytics Data Engineer to build a Curated, Accurate, Reliable data lake — a governed lakehouse with point-in-time and near-real-time pipelines, and a clear semantic layer — so teams trust and use data to help drive operational and business decisions.

You will ultimately be part of a collaborative team that's responsible for understanding how well our products work, advocating for critical changes, and representing how they'll be experienced by our customers. We deliver descriptive, diagnostic, prescriptive, and predictive analytics that show what’s happening, explain why, recommend what to do, and empower decision making automation. We publish certified metrics and models used in executive-facing reports, raising product quality, accelerating releases, and reducing risk across all Apple platforms and locales. As a member of our passionate group in Siri, you will have the unique and rewarding opportunity to shape and improve our products to delight and inspire millions of Apple's customers every day.

Minimum Qualifications

• 5+ years in data engineering; expert SQL and Python knowledge

• Deep Spark experience (batch + structured streaming)

• Hands-on experience with a modern data lake technology: Iceberg or equivalent of object storage

• Proven pipeline orchestration (Airflow or equivalent) and Git-based delivery

• Strong data modeling, governance, lineage, and reliability practices

Preferred Qualifications

• Spark Streaming, Kafka, Flink or similar streaming; near-real-time analytics

• Data-quality frameworks and observability

• Experience with feature stores and ML data pipelines

• BS/MS in an engineering or a related field (or equivalent)

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .