Azure Cloud Infrastructure Engineer (Pulumi | Python | IaC)

Job Overview

Location
Remote, Any Country
Job Type
Full Time
Date Posted
20 days ago

Additional Details

Job ID
1796
Job Views
78

Job Description

Please send resume at : [email protected] , cc: [email protected]

About the Role

We are seeking a contract-based Pulumi Infrastructure Engineer to support the setup and automation of cloud infrastructure . The role involves developing and maintaining Infrastructure as Code (IaC) using Pulumi (Python) on Microsoft Azure, covering environments for development, QA, and production. The engineer will work closely with our backend, data, and ML teams to ensure all Azure resources are provisioned securely, efficiently, and in line with our environment standards


Key Responsibilities

• Implement and maintain Infrastructure as Code (IaC) using Pulumi (Python) for Azure environments.

• Deploy, configure, and manage Azure Container Apps, ACR, CosmosDB, Redis Cache, Key Vault, Synapse Analytics, and ML Workspaces.

• Configure Azure Blob Storage for Pulumi state management and ensure secure handling.

• Manage Resource Groups, networking, and RBAC permissions for multi-environment setups. • Integrate Pulumi with CI/CD pipelines for automated provisioning.

• Support environment setup scripts (Bash/ZSH/Fish) and environment variables.

• Document deployment workflows and maintain repository organization.

• Troubleshoot provisioning issues and optimize configurations


Required Skills & Experience

• Strong written and spoken English language skills

• 3+ years in Azure Cloud Infrastructure and IaC.

• Proven experience with Pulumi (Python) or Terraform + Python.

• Strong understanding of Azure Resource Management, Networking, and Identity Management.

• Experience with Azure CLI, Pulumi CLI, and scripting.

• Knowledge of containerized workloads (Docker, ACR, ACA).

• Experience managing state files in Azure Blob Storage.

• Strong grasp of infrastructure security best practices.

• Proficient with Git and CI/CD workflows

• Familiarity with Azure ML workspace provisioning.

• Background in Python automation or data platform infrastructure.

• Experience with Azure Synapse and Data Lake Storage Gen2.


Location

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