Engineer, Storage Engineering
Indexed description
This role requires someone who can think like a developer, automate like a DevOps engineer, and is comfortable with storage and backup engineering.
Responsibilities
- Python Automation & Engineering
- Design and develop enterprise-grade Python automation frameworks, modules, and reusable libraries for storage and backup provisioning, lifecycle management, telemetry ingestion, and API integrations.
- Integrate Python with REST APIs exposed by storage vendors, monitoring tools, CMDBs, and internal services.
- Perform complex data analytics and transformation logic to drive intelligent automation decisions.
- Ansible Automation
- Architect and maintain Ansible automation for configuration management, provisioning, compliance, and change execution.
- Build Ansible collections, modules, roles, dynamic inventories, and reusable playbooks specifically for enterprise storage and SAN infrastructures.
- Integrate Ansible with CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI).
- Apply Ansible best practices such as idempotency, YAML structuring, and Ansible-lint compliance.
- N8N Workflow Orchestration
- Architect advanced n8n automation pipelines that connect APIs, databases, webhooks, and storage platforms.
- Build multi-step workflows for alert enrichment, automated responses, ticketing integration, and data orchestration.
- Implement error-handling, retries, conditional branches, and webhook-driven flows.
- Integrate n8n with Python scripts, REST endpoints, and event-driven triggers.
- Optimize workflow performance, scalability, modularity, and maintainability.
- Automation & Infrastructure Engineering
- Build automation pipelines across provisioning, monitoring, compliance, reporting, and remediation workflows.
- Implement full lifecycle orchestration for block, file, and object storage platforms.
- Develop infrastructure-as-code for storage-related tasks where feasible (Ansible, Terraform, native vendor APIs).
- Automate operational tasks including host registration, zoning, data collection, capacity forecasting, and system health checks.
- Develop self-healing automation using event-driven triggers and AI-based decision engines.
- DevOps, Tooling, and Software Engineering
- Use Git, branching strategies, PR workflows, and code reviews to maintain clean, stable, production-ready automation repositories.
- Integrate automation components with CI/CD tools (Jenkins, GitHub Actions, GitLab CI, etc.).
- Build automated test harnesses for scripts, APIs, and workflows using pytest or similar frameworks.
- Maintain end-to-end observability using logging, metrics, dashboards, and alerting.
- AI and Intelligent Automation
- Integrate LLM-based tools to generate, validate, or optimize code and configuration.
- Build AI-assisted anomaly detection using log or telemetry data.
- Develop AI-augmented workflows in n8n or Python for intelligent alerting and decision-making.
- Experience with agent frameworks, embeddings, or vector databases is a plus.
- Data, Visualization & Analytics
- Strong SQL skills for automation involving databases or CMDBs.
- Experience with Grafana, Tableau, or similar tools to generate automated dashboards.
- Ability to create pipelines that continually ingest, normalize, and present storage telemetry data.
- Experience with containerization (Docker) and orchestration (Kubernetes).
- Familiarity with cloud storage platforms (AWS S3, Azure Blob, GCP Storage).
- Experience with Infrastructure-as-Code for storage automation.
- Background in workflow engines such as Rundeck.
Create a free Caio profile to unlock more results and save your role and location preferences.
Unlock free search