As an Azure Cloud Engineer, you will:
- Design, develop, and maintain cloud solutions using Azure technologies.
- Implement and optimize CI/CD pipelines using Azure DevOps, Git, and YAML pipelines.
- Manage Azure resources, including Azure Data Factory, Cosmos DB, SQL Server, PostgreSQL, and Azure Active Directory.
- Troubleshoot and resolve issues in running cloud applications, ensuring high availability and performance.
- Work in an Agile and DevOps environment, collaborating with teams using Scrum and Kanban methodologies.
- Implement and maintain cloud infrastructure using Azure Resource Manager (ARM), Azure Bicep, and cloud design patterns.
- Oversee risk management, service monitoring, and eliminating technical debt in cloud environments.
- Work with Azure Function Apps, Logic Apps, Service Bus, API Management, Virtual Machines, Azure Bastion, and other key Azure services.
What You Bring to the Table:
- Minimum Bachelor's degree in a relevant field (B ICT).
- Substantive knowledge of Azure Cloud technologies and cloud design patterns.
- Minimum of 2 Azure certifications (Solutions Architect, Azure Administrator, DevOps Engineer, or Azure Security Technologies).
- At least 2 years of experience with Azure development and Agile/DevOps methodologies (Scrum & Kanban).
- Experience with programming or scripting languages like Bash and PowerShell.
- Strong knowledge of CI/CD practices and cloud-native development.
You should possess the ability to:
- Configure, use, and maintain CI/CD pipelines in Azure.
- Work with Azure DevOps, Git, and YAML pipelines for seamless delivery.
- Troubleshoot and resolve cloud application issues.
- Manage cloud resources and policies efficiently.
- Collaborate effectively in Agile and DevOps environments.
What we bring to the table:
- A dynamic environment where cloud administration and operation are prioritized.
- Opportunities to work with advanced Azure technologies, including container solutions (AKS, ACI), and networking concepts (VNET, Subnets, NSGs).
- Exposure to cutting-edge cloud applications, risk mitigation processes, and the ability to contribute to machine learning, data warehousing, and ETL developments.