2 months ago
Responsibilities
- Develop and operate large-scale big data platforms for analytics, reporting, and AI/ML applications.
- Optimize platform performance and cost while automating operational processes.
- Identify, troubleshoot, and resolve production errors and incidents through root cause analysis.
- Design, build, and operate distributed systems with low latency, fault tolerance, and high availability.
- Manage multi-tenant Kubernetes clusters and debug Kubernetes and Spark issues.
- Build reusable software frameworks or libraries across the development lifecycle.
Requirements
- 3+ years of professional software engineering experience with large-scale big data platforms.
- Strong programming skills in Java, Scala, Python, or Go.
- Expertise operating large-scale distributed data processing systems, especially Apache Spark.
- Hands-on experience with table formats and data lake technologies such as Apache Iceberg.
- Strong incident management, troubleshooting, root cause analysis, and performance optimization experience.
- Proficiency with cloud technologies including AWS and GCP.
- Experience with Unix/Linux systems and command-line debugging tools.
- Preferred: experience with multi-cloud infrastructure, Kubernetes at scale, Airflow, DBT, data modeling, data warehousing, GPUs, MLFlow, LLMs, open source contributions, and reusable frameworks or libraries.
Tech Stack
Categories
Data EngineeringSite Reliability
About Apple
Apple designs and sells consumer electronics, software, and services for consumers and professionals worldwide, including iPhone, Mac, iPad, Apple Watch, and AirPods, plus platforms like iOS/macOS and services such as the App Store, iCloud, Music, and TV+. Its business combines device sales with services and subscriptions and in-house silicon design. Founded in 1976, Apple is headquartered in Cupertino, California, and trades on NASDAQ as AAPL.