Data Engineer

Apple; Cupertino (CA); On-site; USD 129,000 - 195,000; Full time

Benefits offered by this job

Medical and dental coverage

Retirement benefits

Discounted products & free services

Tuition reimbursement

Apple stock purchase eligibility

Discretionary RSU awards

Relocation assistance

Job summary

Apple in Cupertino seeks a Data Engineer to build privacy-focused data and ML systems across real-time, near-real-time, and batch workflows. You will own components from pipeline design to deployment, with privacy and correctness at the forefront.

The role emphasizes reliability, performance, and cost efficiency while leveraging LLMs like Claude and Gemini daily to accelerate development. 1+ years of experience and BS/MS required.

Qualifications

• 1+ years of experience building scalable data pipelines and ML systems.
• Strong computer science and software engineering fundamentals.
• Proficiency in 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 technical and non-technical teams.
• Hands-on experience using LLMs (Claude, Gemini) in daily engineering work.
• Excellent collaboration skills.
• BS/MS in Computer Science, Software Engineering, Distributed Systems, or a related field.

Responsibilities

• Engineer secure, scalable data and machine learning systems across real-time, near-real-time, and batch execution 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, including privacy-preserving infrastructure.
• Improve reliability, performance, and efficiency through schema changes, backfills, and testing infrastructure (including A/B testing).
• Apply understanding of business, analytics, and engineering to deliver reusable, efficient solutions.
• Use LLMs and AI coding agents daily to accelerate coding, testing, and debugging while validating results for correctness and privacy.
• Contribute in an Agile, sprint-based environment emphasizing reliability and scalability.
• Participate in on-call and incident response with senior support for root-cause analysis.
• Collaborate with cross-functional partners and mentor others as you advance.

Skills

1+ years exp

CS fundamentals

Rust

Python

Java

Scala

Distributed systems

Data structures & algorithms

LLMs

Communication

Collaboration

Education

BS/MS in CS or related field

Tools

Spark

Kafka

Iceberg

Flink

Rust

Python

Java

Scala

Claude

Gemini

Job description

Build privacy-focused data engineering and machine learning systems for Apple Ads inside Apple’s Data Organization. This onsite role in Cupertino, CA blends real-time, near-real-time, and batch advertising capabilities with scalable engineering, reliability improvements, and hands-on use of LLMs and AI coding agents to accelerate implementation and debugging.

As a Data Engineer, you will design and deliver core data and ML components, strengthen pipeline performance and dependability, and support mission-critical infrastructure that must meet privacy and correctness expectations. You will collaborate with product managers and world-class engineers through code and design reviews, contribute to incident response, and grow your impact over time.

Compensation: USD 129,300 - 194,700 per year. Minimum experience: 1+ years. Education: BS/MS in Computer Science, Software Engineering, Distributed Systems, or a related field.

What you’ll do

• Engineer secure, scalable data and machine learning systems across real-time, near-real-time, and batch execution 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, including privacy-preserving infrastructure
• Improve reliability, performance, and efficiency through schema changes, backfills, and the experimentation and testing infrastructure (including A/B testing) to validate updates
• Apply a 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 to accelerate coding, testing, and debugging, while continuously validating results for correctness, privacy, and cost
• Contribute in an Agile, sprint-based environment that emphasizes reliability, resiliency, extensibility, scalability, and productivity
• Participate in on-call, monitoring, and ongoing reliability and efficiency improvements, with more senior support for incident response and root-cause analysis
• Collaborate with cross-functional partners and grow through code and design reviews, including mentoring others as you advance

What you bring

• 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 technical and non-technical teams
• Hands-on experience using LLMs (e.g., Claude, Gemini) in daily engineering work, including code generation, review, debugging, test writing, agentic loops, and evaluation systems to improve software engineering skills and velocity
• Excellent collaboration skills
• BS/MS in Computer Science, Software Engineering, Distributed Systems, or a related field

Technologies you’ll work with

Spark, Kafka, Iceberg, Flink, Rust, Python, Java, Scala, LLMs, Claude, Gemini, A/B testing

Benefits at Apple

• Comprehensive medical and dental coverage
• Retirement benefits
• A range of discounted products and free services
• Reimbursement for certain educational expenses, including tuition
• Opportunity to become an Apple shareholder through Apple’s discretionary employee stock programs
• Discretionary restricted stock unit awards
• Ability to purchase Apple stock at a discount through the Employee Stock Purchase Plan if voluntarily participating
• 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 with rapidly changing environments and ambiguous requirements
• Prior experience in the advertising industry (huge plus)