Cloud Storage Systems Engineer - Scale, Reliability & Automation

NetApp; San Jose (CA); On-site; USD 180,000 - 210,000; Full time

Benefits offered by this job

Health Insurance

Employee stock purchase plan

RSUs

Job summary

NetApp is seeking engineers for the Azure NetApp Files (ANF) team to build and operate cloud-scale distributed systems across storage, networking, and cloud infrastructure. Role spans development, validation, performance, and reliability with AI-native practices.

The team emphasizes ownership from design through production and collaboration across disciplines in a fast-paced environment.

Qualifications

• 6–8 years of software or systems engineering experience, including data management/storage.
• Proficiency in Go; experience with Python for automation and testing.
• Experience with cloud-native distributed systems and Kubernetes.
• Familiarity with RESTful APIs and cloud platforms (Azure/AWS/GCP).

Responsibilities

• Own design, development, performance, and reliability of data-plane services.
• Lead features through the full software lifecycle from architecture to production support.
• Design, develop, and operate cloud-native distributed systems with microservices and CI/CD.
• Build scalable back-end services, APIs, and service integrations with automation and observability.
• Drive code quality, testing, security, and continuous improvement.
• Collaborate with product, architects, and cross-functional teams to deliver end-to-end solutions.
• Mentor team members and contribute to technical growth.

Skills

Go

Python

Distributed systems

Cloud storage

Kubernetes

RESTful APIs

CI/CD

Observability

Security practices

Communication

Education

Bachelor’s degree in Computer Science, Engineering, or related field

Master’s degree in Computer Science or related field

Tools

Kubernetes

Docker

CI/CD tooling

Job description

NetApp is seeking engineers for the Azure NetApp Files (ANF) team to build and operate cloud-scale distributed systems across storage, networking, and cloud infrastructure. Role spans development, validation, performance, and reliability with AI-native practices.

The team emphasizes ownership from design through production and collaboration across disciplines in a fast-paced environment.