Senior Data Engineer

As part of Apple Services Engineering, you’ll help power the Device Compute Analytics team by building and owning a data lakehouse that turns device and compute events into accurate, timely, fast-to-query tables. This onsite role in Cupertino, CA also offers a compensation range of USD 184,700 - 324,800 per year, along with comprehensive benefits and opportunities tied to Apple equity programs.

You’ll take on end-to-end data engineering work, from Spark pipeline development to designing Apache Iceberg tables that are queried via Trino. Over time, you’ll also assume ingestion ownership from Kafka, while strengthening trust in the data through quality checks and monitoring.

Responsibilities

• Own the data lakehouse that converts raw device and compute events into reliable, fast-to-query tables.
• Build and run Apache Spark pipelines, design analytics tables queried through Trino, and implement checks to keep data accurate and timely.
• Gradually take over ingestion of events from Kafka.
• Turn device lifecycle, job and session activity, provisioning, and failure events into datasets that teams can trust and build on.
• Collaborate with a data analyst and a full-stack engineer (who builds dashboards), plus application engineers and other teams across Apple.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 7+ years of professional data engineering experience building production data pipelines at scale, including diagnosing and improving performance of data jobs and queries, or an equivalent advanced degree plus experience.
• Production experience with Apache Spark, including both batch and streaming (Structured Streaming) pipelines.
• Strong data modeling skills, including experience designing analytics schemas on Apache Iceberg or comparable lakehouse table formats.
• Proficiency in Java or Scala, and strong SQL.
• Experience building data quality checks and monitoring for production pipelines, including freshness and completeness alerting and reconciliation between source and derived data.
• Productive use of AI coding tools in real delivery, with the discipline to validate generated code and queries.
• Excellent communication and critical thinking in a team environment.

Benefits

• Comprehensive medical and dental coverage.
• Retirement benefits.
• A range of discounted products and free services.
• Reimbursement for certain educational expenses, including tuition.
• Discretionary bonuses or commission payments, as well as relocation (if eligible).
• Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs.
• Eligibility for discretionary restricted stock unit awards.
• Ability to purchase Apple stock at a discount when voluntarily participating in Apple’s Employee Stock Purchase Plan.

Technologies: Apache Spark, Structured Streaming, Apache Iceberg, Trino, Kafka, SQL, Java, Scala.

Preferred Qualifications

• Production experience with Apache Kafka as a streaming source.
• Production experience with Apache Flink, including the Iceberg sink, exactly-once delivery, and stateful jobs on Kubernetes.
• Experience with data contracts and schema management as code (for example schema registries or dbt model contracts).
• Experience tuning tables and queries for a distributed SQL engine such as Trino.
• Experience with workflow orchestration and Python automation.
• Experience building dashboards or data applications that present data to users, with attention to visual design.
• Experience owning the design of a data platform or pipeline, not just implementing it.
• Experience mentoring engineers and leading cost or reliability improvements.