Senior Data Engineer

Based in Cupertino, California and working onsite, this role from Apple offers a compelling benefits package alongside a competitive salary. The compensation range is USD 172,100 to 305,600 per year. Employees receive comprehensive medical and dental coverage, retirement benefits, access to discounted products and free services, tuition reimbursement, discretionary employee stock programs, eligibility for discretionary restricted stock unit awards, the ability to purchase Apple stock at a discount through the Employee Stock Purchase Plan, discretionary bonuses or incentive payments, and relocation support.

As a Senior Data Engineer at Apple, you will design and deploy AI-ready data pipelines that fuel analytics across Music, Video, and Books. The position blends rigorous systems engineering with strategic collaboration, aiming to build extensible, modular data infrastructure that scales to meet enterprise demands.

Responsibilities

• Build and scale data infrastructure: design and deploy modular, scalable pipelines optimized for massive scale, delivering reliable, self-service data products with clear contracts and SLAs for internal teams, data scientists, and external partners.
• Champion AI and innovation: identify and embed AI-enabled tools and intelligent automation, exploring LLMs, RAG pipelines, and emerging technologies to raise capabilities and operational efficiency.
• Drive data quality and observability: develop validation frameworks, automated data assertions, lineage tracking, anomaly detection, and monitoring to ensure transparency and reliability across production data flows.
• Enable advanced analytics: partner with data scientists, analysts, and cross-functional stakeholders to provide structured, high-performance datasets backed by clear SLAs, reducing ad hoc engineering requests.
• Cross-functional partnership: collaborate across Analytics, Operations, Engineering, and Partner teams, translating requirements into resilient engineering solutions aligned with business priorities.
• Operational excellence and self-service: guide the team toward scalable, self-service analytics, enforce CI/CD practices, mentor peers, and foster a culture focused on quality, reliability, and continuous improvement.

Requirements

• 7+ years of professional experience in data engineering or systems architecture, with a track record of owning production data systems at massive scale and processing billions of records.
• Advanced Python and SQL skills, with expertise in distributed data processing (PySpark/Spark), modular software design, and automated testing.
• Hands-on experience designing and operating CI/CD pipelines, automated deployment workflows, and version-controlled data infrastructure.
• Proven expertise in data quality management, resolving 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 technical solutions.
• Exceptional written and verbal communication skills, capable of articulating complex technical concepts to non-technical audiences and influencing stakeholders at all levels.
• Strong logical reasoning, critical thinking, and complex problem-solving abilities.
• Bachelor's Degree in Computer Science, Data Engineering, Information Systems, or a related technical field.

Technologies

• Python, SQL
• PySpark, Spark
• Apache Iceberg, Delta Lake
• Tableau, Superset
• SPARQL, Graph databases
• LLMs, RAG pipelines