Data Engineer, Privacy-Focused Data Platforms

Apple; Cupertino (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Apple Ads is building next‑gen privacy‑focused advertising data capabilities. You will work in data engineering to design, deploy, and optimize data pipelines and ML components at scale, applying privacy‑preserving practices across real‑time and batch workflows.

Join a team of engineers and product managers to drive reliable, efficient data platforms. Expect collaboration in a fast‑moving Agile environment and opportunities to mentor others as you grow.

Qualifications

• 1+ years of industry experience building scalable data pipelines and ML systems, or other distributed software
• Strong CS fundamentals and software engineering skills
• Proficiency in Rust, Python, Java, or Scala
• Experience with Spark, Kafka, Flink or similar
• Experience with on‑prem and cloud deployments
• Understanding of data structures, algorithms, and system design
• Ability to communicate across technical and non‑technical teams
• Hands-on experience using LLMs in daily work and debugging
• BS/MS in CS, Software Engineering, or Distributed Systems

Responsibilities

• Engineer secure, scalable data and ML systems across real-time and batch contexts
• Own design and delivery of core components from pipeline to model deployment
• Improve reliability, performance, and efficiency of data systems
• Collaborate with engineers and product managers and mentor others
• Contribute to on-call, monitoring, and incident response
• Work in a sprint-based Agile environment emphasizing reliability and scalability

Skills

Data pipelines

Machine learning systems

Rust

Python

Java

Scala

Spark

Kafka

Flink

LLMs

Cloud

On‑prem

Algorithms

System design

Team collaboration

BS/MS in CS

Education

BS in Computer Science

MS in Computer Science

Tools

Iceberg

NoSQL databases

Job description

Apple Ads is building next‑gen privacy‑focused advertising data capabilities. You will work in data engineering to design, deploy, and optimize data pipelines and ML components at scale, applying privacy‑preserving practices across real‑time and batch workflows.

Join a team of engineers and product managers to drive reliable, efficient data platforms. Expect collaboration in a fast‑moving Agile environment and opportunities to mentor others as you grow.