Data Engineer
Artificial Intelligence
Big Data
Bigdata
Data
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Iceberg
Data Integration
Data Integration Tools
Data Pipeline
Data Pipelines
Data Platform
Data Processing
Data Science
Database
Databases
Engineer
ETL
Event Driven Architecture
Flink
Informatica
Information Technology (IT)
Software Development
Spark
SQL
Stream Processing
Streaming Data
Job Description
Build privacy-focused data engineering and machine learning systems for advertising at Apple Ads within the Data Org.
Responsibilities
- Engineer secure, scalable data and machine learning systems for real-time, near-real-time, and batch processing using Spark, Kafka, Iceberg, and related technologies
- Own end-to-end delivery of core components, from pipeline architecture to ML model development, training, and deployment
- Design and support privacy-preserving, mission-critical data and ML infrastructure
- Improve reliability, performance, and efficiency across systems, including schema changes and backfills
- Build and maintain experimentation and testing infrastructure to validate changes (including A/B testing)
- Apply strong understanding of the intersection between business, analytics, and engineering to deliver reusable, efficient solutions
- Use LLMs and AI coding agents (e.g., Claude, Gemini) daily for implementation, testing, and debugging while validating results for correctness, privacy, and cost
- Collaborate with engineers and product managers through code and design reviews; mentor others as seniority increases
- Participate in on-call, monitoring, and continuous reliability and efficiency improvements; more senior engineers lead incident response and root-cause analysis
- Work in an Agile, sprint-based environment with emphasis on reliability, resiliency, extensibility, scalability, and productivity
Requirements
- 1+ years of industry experience building scalable data pipelines and machine learning systems, or other distributed software at scale
- Strong computer science and software engineering fundamentals
- Proficiency in modern programming languages such as Rust, Python, Java, or Scala
- Experience with distributed systems and data processing technologies, such as Spark, Kafka, Flink
- Experience building and scaling systems on premise and in the cloud
- Solid understanding of data structures, algorithms, and system design
- Ability to communicate effectively with cross-functional teams (technical and non-technical)
- Hands-on experience using LLMs (e.g., Claude, Gemini) for daily engineering work including code generation, review, debugging, test writing, agentic loops, and evaluation systems
- Excellent collaborative skills
- BS/MS in Computer Science, Software Engineering, Distributed Systems, or a related field
Technologies
- Spark
- Kafka
- Iceberg
- Flink
- Rust
- Python
- Java
- Scala
- LLMs
- Claude
- Gemini
- A/B testing
Benefits
- Comprehensive medical and dental coverage
- Retirement benefits
- Discounted products and free services
- Reimbursement for certain educational expenses, including tuition
- Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
- Discretionary restricted stock unit awards
- Purchase Apple stock at a discount with participation in Apple’s Employee Stock Purchase Plan
- Discretionary bonuses or commission payments (as applicable)
- Relocation (as applicable)
Preferred Qualifications
- Experience with NoSQL datastores (e.g., Cassandra, Keyspaces, ElastiCache)
- Experience with lakehouse and Iceberg table formats
- Experience with anomaly detection
- Experience with A/B experimentation frameworks
- History of driving reliability, efficiency, or cost improvements, and mentoring other engineers
- Comfort working in a rapidly changing environment with ambiguous requirements
- Prior experience in the advertising industry (huge plus)
Location: Cupertino, CA (onsite)
Salary: USD 129,300 - 194,700 per year
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