Senior Data Engineer — Music Services Operations Analytics & Strategy

The Music Services Operations Analytics u0026 Strategy team builds the intelligence infrastructure that powers Apples 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.

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.

Build u0026 Scale Data Infrastructure: Architect and deploy scalable modular data pipelines optimized for Apple Musics massive scale delivering reliable self-service data products with clear contracts and SLAs that internal teams data scientists and external partners can confidently AI u0026 Innovation: Proactively identify and integrate AI-enabled tools intelligent automation and advanced analytics workflows into existing data systems. Actively explore how LLMs RAG pipelines and emerging technologies can elevate team capabilities and drive operational efficiency. Champion best practices for AI-augmented data engineering across the Data Quality u0026 Observability: Build robust validation frameworks to sanitize unpredictable third-party and provider feeds. Implement automated data assertions lineage tracking advanced anomaly detection and monitoring to guarantee full transparency and reliability across the production data Advanced Analytics: Partner closely with data scientists analysts and cross-functional stakeholders to deliver structured high-performance datasets backed by clear SLAs accelerating insights and systematically reducing dependency on ad-hoc engineering -Functional Partnership: Collaborate and communicate effectively across Analytics Operations Engineering and Partner teams. Act as a proactive technical partner to the business translating ambiguous requirements into resilient engineering solutions that align with organizational Excellence u0026 Self-Service: Lead the teams evolution toward scalable self-service analytics. Enforce strict CI/CD practices mentor peers and foster a strong data engineering culture centered on quality reliability and continuous improvement.n

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 environmentsnAdvanced proficiency in Python and SQL with expertise in distributed data processing frameworks (e.g. PySpark/Spark) modular software design and automated testing methodologiesnExtensive hands-on experience designing and operating CI/CD pipelines automated deployment workflows and version-controlled data infrastructurenProven expertise in data quality management resolving complex taxonomy mapping issues and implementing programmatic anomaly detection on high-volume datasetsnProven ability to lead projects influence cross-functional teams and drive consensus in a matrixed organization translating stakeholder needs into scalable well-scoped technical solutionsnExceptional written and verbal communication skills with the ability to articulate complex technical concepts to non-technical audiences and effectively influence stakeholders at all levelsnExceptional aptitude for logical reasoning critical thinking and complex problem-solvingnBachelors Degree in Computer Science Data Engineering Information Systems or a related technical field

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 objectivesnA 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 toolingnExperience 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 outputnDeep familiarity with open table formats (Apache Iceberg Delta Lake) cloud-native data systems and self-service data platform principles including data mesh architecturesnFamiliarity with graph databases and SPARQL as a forward-looking capabilitynDemonstrated expertise implementing data privacy frameworks including hands-on experience building systems compliant with global regulations (e.g. GDPR CCPA)nProficiency 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 audiencesnFamiliarity with the structural nuances of diverse digital media catalogs audio video and publishing data modelsnExperience mentoring peers and championing a culture of data engineering excellence across the teamnA 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