Senior Data Engineer
Senior
Apache Spark
Big Data
Bigdata
Data
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Engineering
Data Integration
Data Integration Tools
Data Lake
Data Lakehouse
Data Pipeline
Data Pipelines
Data Platform
Data Processing
Data Warehouse
Database
Databases
ETL
Event Driven Architecture
Iceberg
Informatica
Kafka
Spark
SQL
Stream Processing
Streaming Data
Structured Streaming
Job Description
Apple Services Engineering’s Device Compute Analytics team is hiring a Senior Data Engineer to build and operate a data lakehouse that converts device and compute events into accurate, timely, fast-to-query tables.
Responsibilities
- Own a data lakehouse that transforms raw device and compute events into reliable, fast-to-query tables
- Build and run Apache Spark pipelines
- Design analytics tables queried via Trino for downstream dashboards
- Implement data quality checks to keep data accurate and timely
- Over time, take over event ingestion from Kafka
- Create trustworthy datasets from device lifecycle, job and session activity, provisioning, and failures events landing in Iceberg
- Collaborate with a data analyst and a full-stack engineer responsible for dashboards, plus application engineers and cross-functional 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 equivalent advanced degree plus experience
- Production experience with Apache Spark, including batch and Structured Streaming
- Strong data modeling skills, including 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 discipline to validate generated code and queries
- Excellent communication and critical thinking in a team environment
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 for 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
Benefits
- Comprehensive medical and dental coverage
- Retirement benefits
- 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 if voluntarily participating in Apple’s Employee Stock Purchase Plan
Location: Cupertino, CA (onsite)
Salary: USD 184,700 - 324,800 per year
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