Junior Python Automation Engineer

About the Role

As a Junior Python Automation Engineer, you will be instrumental in designing, implementing, and maintaining comprehensive automated tests. This includes functional, upgrade, high availability, negative, and longevity test scenarios. You will develop modular, reusable, and resilient test automation code to ensure the stability of our systems. Your responsibilities will also involve creating verification plans, test strategies, and triage playbooks, identifying coverage gaps, and enhancing the reliability of our automation infrastructure. A key aspect of this role will be automating testing across various storage platforms such as Object Storage, NAS, SAN, and File Systems. You will test and debug REST APIs, backend services, and cloud workflows integrated with CI/CD pipelines, particularly Jenkins. Furthermore, you will analyze system logs, conduct failure injection testing, and actively collaborate with development teams to facilitate defect resolution.

What Makes This Role Exciting

• Work at the forefront of automation and large-scale storage technology, tackling complex infrastructure challenges.
• Gain the opportunity to design frameworks that significantly enhance product reliability and deployment efficiency.
• Collaborate with leading engineers in an innovative, agile environment.
• Enjoy the freedom to experiment with diverse automation design patterns and scalability solutions.

What We're Looking For

• Strong hands-on experience in Python automation, coupled with a deep understanding of algorithms, data structures, and fundamental OS concepts (Linux/Windows).
• Expertise in Pytest, Jenkins CI, and Git-based workflows, including fixtures, parametrization, and parallelization.
• Proven experience in testing distributed systems or storage/networking platforms (e.g., iSCSI/NVMe-TCP, NFS/SMB, S3).
• A solid grasp of REST APIs and backend validation.
• Excellent debugging and triage skills across product, environment, and automation layers.

Bonus Skills

• Exposure to cloud platforms like AWS, Azure, or GCP.
• Experience with containerized environments such as Docker/Kubernetes.
• Knowledge of performance or scalability testing tools.
• Familiarity with infrastructure-as-code principles and DevOps pipelines.