Senior Data Engineer - Music Services Operations Analytics & Strategy

Cupertino, CA, US • Posted 30+ days ago • Updated 8 hours ago
Full Time
On-site
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Management
  • Analytical Skill
  • Dimensional Modeling
  • Leadership
  • Analytics
  • Systems Engineering
  • Partnership
  • Collaboration
  • Video
  • Systems Architecture
  • Python
  • SQL
  • Data Processing
  • PySpark
  • Apache Spark
  • Software Design
  • Automated Testing
  • Continuous Integration
  • Continuous Delivery
  • Data Quality
  • Taxonomy
  • Mapping
  • Communication
  • Articulate
  • Reasoning
  • Critical Thinking
  • Conflict Resolution
  • Problem Solving
  • Computer Science
  • Information Systems
  • Data Architecture
  • Artificial Intelligence
  • Workflow
  • Apache HTTP Server
  • Cloud Computing
  • Graph Databases
  • SPARQL
  • Privacy
  • Data Visualization
  • Reporting
  • Tableau
  • Digital Media
  • Audiovisual
  • Publishing
  • Mentorship
  • Data Engineering
  • Media
  • Music

Summary

The Music Services Operations Analytics & Strategy team builds the intelligence infrastructure that powers Apple's media services. Processing billions of records monthly, we manage complex content taxonomies, variable provider data, and hundreds of analytical dimensions - delivering accurate, actionable insights to cross-functional teams, partner organizations, and executive leadership.

Description

We are seeking a Senior Data Engineer to architect and deploy the robust, AI-ready data pipelines that serve as the foundation for our analytics capabilities. This role demands both deep systems engineering rigor and strong business partnership - the ideal candidate brings battle-tested experience at massive scale and the strategic foresight to build extensible, modular systems that span across Music, Video, and Books.

Minimum Qualifications

7+ years of professional experience in data engineering or systems architecture, with a demonstrated history of owning production data systems at massive scale - processing billions of records in complex, high-volume environments

Advanced proficiency in Python and SQL, with expertise in distributed data processing frameworks (e.g., PySpark/Spark), modular software design, and automated testing methodologies

Extensive hands-on experience designing and operating CI/CD pipelines, automated deployment workflows, and version-controlled data infrastructure

Proven expertise in data quality management, resolving complex taxonomy mapping issues, and implementing programmatic anomaly detection on high-volume datasets

Proven ability to lead projects, influence cross-functional teams, and drive consensus in a matrixed organization - translating stakeholder needs into scalable, well-scoped technical solutions

Exceptional written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical audiences and effectively influence stakeholders at all levels

Exceptional aptitude for logical reasoning, critical thinking, and complex problem-solving

Bachelor's Degree in Computer Science, Data Engineering, Information Systems, or a related technical field

Preferred Qualifications

Strategic mindset with the ability to define long-term data architecture vision, anticipate upstream and downstream challenges, and make data-informed decisions aligned with broader organizational objectives

A resourceful, action-oriented innovator who consistently cuts through ambiguity and engineers creative solutions - particularly through the application of AI-driven technologies, intelligent automation, and emerging data tooling

Experience leveraging AI-enabled tools and workflows within data engineering contexts - including familiarity with LLMs, RAG pipelines, and intelligent automation - with a demonstrated ability to apply these technologies to meaningfully improve speed, quality, and operational output

Deep familiarity with open table formats (Apache Iceberg, Delta Lake), cloud-native data systems, and self-service data platform principles including data mesh architectures

Familiarity with graph databases and SPARQL as a forward-looking capability

Demonstrated expertise implementing data privacy frameworks - including hands-on experience building systems compliant with global regulations (e.g., GDPR, CCPA)

Proficiency with data visualization and reporting tools such as Tableau, Superset, or equivalent platforms - with an ability to translate complex data into clear, consumable insights for business audiences

Familiarity with the structural nuances of diverse digital media catalogs - audio, video, and publishing data models

Experience mentoring peers and championing a culture of data engineering excellence across the team

A genuine passion for Apple products and services, with deep familiarity with the Apple ecosystem and an understanding of the content and media landscape that drives Apple Music and beyond
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90733111
  • Position Id: 321513d44b70630f7d06a0ab991d7817
  • Posted 30+ days ago
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