Software Data Engineer

Join Apple's Analytics Platforms & Experiences (APX) team as a Software Engineer and be part of a team that is redefining what modern data engineering looks like. APX is part of Apple Services Engineering - the engine that powers App Store, Apple TV+, Apple Music, Apple Podcasts, Apple Books, Fitness+, the iTunes Store, and more. We build the frameworks, tools, and platform solutions that unlock observability, deliver actionable insights, and enable data quality-driven orchestration at massive scale. Our work drives real, measurable gains in efficiency and productivity across some of Apple's most critical services.

As a member of the Data Engineering Platform (DEP) team - the foundational layer of our platform - you will help build scalable backend services and developer tools that make it easier for teams across Apple to build and operate analytics pipelines efficiently. If you are passionate about data engineering, eager to grow, and excited about making a real impact at Apple scale - this is the role for you.

Description

As part of the Data Engineering Platform (DEP) team, you will help design and build the core platform capabilities that teams across Apple rely on every day. You will collaborate closely with experienced engineers, contribute to scalable backend services that integrate big data technologies with microservices, and help shape intuitive developer tools and automation systems that reduce friction and drive productivity. This is a great opportunity for an engineer who wants to grow fast, work on hard problems, and do the best work of their life at Apple.

Minimum Qualifications

Bachelor's degree in Computer Science, Software Engineering, or a related technical field

3+ years of software engineering experience, with a solid foundation in building and shipping production-quality code

Strong proficiency in at least one programming language such as Python, Java, Go, or Scala

Understanding of data engineering fundamentals including data pipelines, batch processing, and real-time data streaming

Hands-on experience designing and building backend services and APIs

Working knowledge of distributed systems and big data technologies such as Spark, Kafka, or Hadoop

Exposure to AI-driven development practices with a genuine enthusiasm for leveraging AI tools to improve engineering productivity and code quality

A curious, self-driven mindset with a strong interest in how AI is shaping the future of software and data engineering

Strong problem-solving ability with a collaborative approach to working across teams

Clear and concise communicator who can translate technical concepts for diverse audiences

Preferred Qualifications

Hands-on experience with big data technologies such as Apache Spark, Kafka, Flink, or Airflow

Some exposure to microservices architecture and cloud platforms such as AWS, Google Cloud Platform, or Azure

Familiarity with data orchestration frameworks and pipeline management tools such as Airflow or Prefect

Basic experience with containerization tools such as Docker and Kubernetes

Awareness of data quality, observability, and monitoring concepts in data pipelines

Some exposure to developer tooling, internal platforms, or automation scripting

Ability to ramp up quickly, take ownership of tasks, and contribute meaningfully in a collaborative team environment