Software Principal Engineer

What youll achieve

We are looking for a highly motivated Software Principal Engineer in Test to join our Power Protect Data Domain product team.

In this role, you will design and implement automation frameworks, develop scalable test solutions, and validate complex distributed storage and data protection systems.

Youll work closely with developers, DevOps, and product managers to ensure our scale-out architecture delivers industry-leading reliability, performance, and customer experience.

You will:

• Design and implement automated test frameworks for large-scale, distributed storage systems.
• Develop, execute, and maintain test suites to validate scale-out architecture, clustering, high availability, and system resilience.
• Simulate real-world customer workloads and failure scenarios to validate product robustness at scale.
• Partner with development teams to embed testability into the design of features.
• Contribute to CI/CD pipelines and tooling to drive faster, higher-quality releases.
• Analyze and debug complex issues in distributed clusters; file detailed defect reports with reproducible steps.
• Continuously improve test coverage, efficiency, and effectiveness through innovation and best practices.
• Collaborate across geographies and functions (QA, DevOps, Support) to deliver end-to-end quality.

Essential Requirements

• Bachelors or masters degree in computer science, Engineering, or a related field. 8+ years in SDET, QA automation, or software engineering roles.
• Strong coding skills in Python, Go Lang or automation scripting languages.
• Experience with distributed systems, clustering, and high availability testing.
• Hands-on experience with Linux, containers (Docker/K8s), and networking fundamentals.
• Proficiency in automation frameworks (PyTest, JUnit, TestNG, or similar). Familiarity with CI/CD pipelines (Jenkins, GitLab CI, or similar).

Desirable Requirements

• Experience testing scale-out storage systems (e.g., Cohesity, Rubrik, NetApp, EMC).
• Knowledge of cloud platforms (AWS, Azure, GCP). Exposure to chaos testing, fault injection, or large-scale system benchmarking.