Senior Data Engineer — Music Services Operations Analytics & Strategy

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$172,100–$305,600 / yr
Posted
4 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $177k
This role $239k
$122k most similar roles pay here $325k

This role pays more than 87% of similar roles. Most pay $141,300–$211,743 — the shaded band above. At the midpoint, this role pays about $239k versus about $177k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1777 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1443 roles with salary data.

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At a glance

TL;DR · Senior Data Engineer — Music Services Operations Analytics & Strategy

As a Senior Data Engineer on the Music Services Operations Analytics & Strategy team at Apple, you will architect and deploy scalable data pipelines for Apple Music's massive scale, integrating AI-enabled tools to enhance operational efficiency. Your daily tasks include building robust validation frameworks, ensuring data quality and observability, and enabling advanced analytics by partnering with cross-functional teams. You must have extensive experience in Python, SQL, PySpark/Spark, and CI/CD practices, along with a strategic mindset for long-term vision and the ability to lead projects at massive scale. This role involves working within a complex content taxonomy environment, processing billions of records monthly, and delivering actionable insights to executive leadership while fostering a culture of data engineering excellence.

What you'll do

  • Build scalable, modular data pipelines optimized for massive scale in complex environments.
  • Integrate AI-enabled tools and advanced analytics workflows into existing data systems.
  • Develop robust validation frameworks to ensure data quality and observability.
  • Deliver high-performance datasets with clear SLAs for internal teams and partners.
  • Lead the team's evolution toward self-service analytics, enforcing CI/CD practices.
  • Mentor peers and foster a strong culture of continuous improvement in data engineering.

What we're looking for

  • 7+ years of professional experience in data engineering or systems architecture at massive scale.
  • Advanced proficiency in Python, SQL, PySpark/Spark, and modular software design.
  • Extensive hands-on experience with CI/CD pipelines and version-controlled data infrastructure.
  • Proven expertise in data quality management and anomaly detection on high-volume datasets.
  • Strong leadership skills to influence cross-functional teams and drive technical solutions.

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