Azure DevOps Engineer

Description :

Key Technical Qualifications :

- Education : Bachelors degree in Computer Science, Software Engineering, or a closely related technical field.

- Cloud Architecture : Deep understanding of both Private and Public Cloud Architectures, with extensive experience specifically on Microsoft Azure.

Infrastructure & Automation :

- Expertise in Azure Services (e.g., Azure DevOps, Azure VMs, Azure Networking, Azure Functions, etc.)

- Proficiency with Infrastructure as Code (IaC) using Terraform for provisioning and managing cloud resources.

- Extensive experience with containerization using Kubernetes for deployment orchestration.

- Familiarity with Service Mesh technologies (e.g., Istio, Linkerd) is highly desirable.

- Expertise with open-source stack technologies relevant to cloud and DevOps.

Scripting & Development :

- Mandatory Hands-on experience in Python scripting for automation, infrastructure management, and tooling development.

- Experience in designing and developing ETL pipelines using languages like Java, Scala, and/or Python.

Key Roles & Responsibilities :

The Azure DevOps Engineer will play a pivotal role in maintaining system reliability, scalability, and efficiency :

1. Cloud Infrastructure and Provisioning :

- Design, implement, and manage secure and scalable cloud infrastructure and services within the Azure environment.

- Utilize Terraform to manage infrastructure as code, ensuring version control, repeatability, and consistency across environments.

- Configure and maintain Kubernetes clusters and related services for application deployment and scaling.

- Apply expertise in networking and security best practices to harden cloud environments.

2. Automation and Scripting :

- Develop and maintain robust automation scripts primarily using Python to streamline operational tasks, infrastructure health checks, and system provisioning.

- Build and optimize CI/CD pipelines using Azure DevOps (or comparable tools) to automate application delivery from code commit to production deployment.

- Implement solutions for logging, monitoring, and alerting (e.g., Azure Monitor, Prometheus, Grafana).

3. Data and Systems Engineering :

- Contribute to the design and implementation of ETL and data pipelines, ensuring efficient data flow and processing.

- Collaborate with development teams to ensure applications are designed for cloud-native deployment and scalability.

- Provide technical guidance and troubleshooting support for complex infrastructure and deployment issues