Staff QA Engineer
DataDirect Networks
Staff QA Engineer
DataDirect Networks
High-performance storage for unstructured data
Job Summary:
We are looking for a Staff QA Engineer to work on validation of high-performance storage solutions for HPC and AI markets. The ideal candidate will have experience designing, implementing, debugging and running both automated and manual software-based tests in a Linux environment, using shell tools and scripts.
Responsibilities for this role include but are not limited to:
• Design and develop both automated and manual test cases to validate product features. Candidate should have more than 12+years of experience in Automation.
• Run automated and manual tests as needed to validate product defect fixes and functionality • Work with the Engineering manager and a geographically distributed team to understand product requirements and features
• Triage test failures on a daily basis
• Contribute to QA reports and provide input on release metrics
• Contribute to and validate product documentation
Qualifications:
• BS/MS in Computer Science, Computer Engineering or equivalent degree/experience.
Candidates should have at least 10+years of experience.
• Strong proficiency in Python and hands on building Test automation frameworks
• Hands-on experience with Linux
• Good knowledge of shell scripting
• Nice to have experience with Robot Framework for test automation
• Hands-on understanding of High Availability (HA) concepts – quorum, failover, failback, etc.
• Strong practical knowledge of Distributed File Systems (e.g., Lustre, GPFS, Ceph) and basic file system concepts
High-performance storage for unstructured data
DDN provides high-performance data storage systems and software for data-intensive environments, including unstructured data, HPC, and AI workloads. Its products combine hardware and software to manage the data lifecycle, with A³I for GPU-optimized AI, EXAScaler as a parallel file system, IntelliFlash hybrid arrays, and Infinia for fast inference. The company differentiates itself through a dedicated focus on HPC/AI storage, close collaboration with NVIDIA, and a strategy of expanding software-defined storage and file systems via acquisitions. Its goal is to help customers scale data storage and AI workloads efficiently across enterprises, government, academia, and cloud providers.
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