Storage DevOps Engineer

Overview MetroSys is seeking a highly skilled Storage DevOps Engineer with strong automation, scripting, and infrastructure-as-code expertise.

This role focuses on building and supporting automation workflows across storage and cloud environments.

The ideal candidate is hands-on, detail-oriented, and comfortable working in fast-moving enterprise environments.

Key Responsibilities Develop and maintain Python automation scripts for storage operations, configuration, and workflow automation.

Build and support Ansible playbooks for storage provisioning, configuration, patching, and operational standardization.

Design and manage Terraform modules for cloud and hybrid infrastructure related to storage, compute, and networking.

Automate processes across storage arrays, backup platforms, and cloud storage environments (Azure, AWS, or GCP).

Collaborate with infrastructure, cloud, and storage engineering teams to streamline deployments and reduce manual operations.

Support CI / CD workflows for infrastructure automation and ensure consistent code quality across environments.

Troubleshoot and optimize automation pipelines, storage integrations, and configuration drift.

Document scripts, playbooks, modules, and processes for repeatability and knowledge sharing.

Required Qualifications 5+ years of experience in automation or DevOps engineering roles.

Strong Python scripting skills (functions, classes, modules, API integrations, error handling).

Hands-on Ansible experience (roles, inventories, automation of storage or infrastructure tasks).

Terraform expertise (modules, workspaces, reusable IaC patterns, cloud integrations).

Experience with storage platforms (Dell, NetApp, Pure, HPE, or cloud storage services).

Solid understanding of cloud infrastructure (Azure, AWS, or GCP).

Familiarity with Git, CI / CD pipelines, and modern DevOps workflows.

Ability to work independently and solve complex automation and infrastructure problems.

Nice to Have Experience with storage data migration tooling.

Exposure to Kubernetes or containerized environments.

Knowledge of monitoring / observability tools (Prometheus, Grafana, Splunk).

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