Cloud Software Engineer — AI-Driven Storage on Azure

NetApp; Munster; Hybrid; EUR 70,000 - 120,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

NetApp's cloud team is driving industry-leading cloud storage services and data infrastructure across Azure, AWS, and Google Cloud. We are building scalable distributed systems spanning storage, networking, cloud infrastructure, and user experience.

We are seeking highly motivated engineers who own design through production and contribute across development, validation, performance, and reliability, with AI-native practices welcomed.

Qualifications

• Proficiency in Python for test automation, validation frameworks, tooling, CI/CD integration, or operational automation.
• Familiarity with C/C++, Go, React, TypeScript, or C# to work across existing service components and user-facing workflows.
• Experience developing RESTful APIs or service-to-service integrations.
• Experience designing, deploying, and operating microservices-based applications using Kubernetes, containers, and modern CI/CD practices.
• Strong software quality practices, including automated testing, performance optimization, and security best practices.
• Experience with observability, monitoring, telemetry, and operational excellence practices.
• Proven ability to build and operate cloud-native distributed systems in Azure, AWS, or GCP.
• Strong aptitude for learning new technologies, paired with excellent written and verbal communication skills and a creative, analytical approach to problem solving.

Skills

Python

C/C++

Go

React

TypeScript

C#

REST APIs

Kubernetes

CI/CD

Observability

Education

BSc or MSc in Electrical Engineering or Computer Science

Job description

NetApp's cloud team is driving industry-leading cloud storage services and data infrastructure across Azure, AWS, and Google Cloud. We are building scalable distributed systems spanning storage, networking, cloud infrastructure, and user experience.

We are seeking highly motivated engineers who own design through production and contribute across development, validation, performance, and reliability, with AI-native practices welcomed.