Azure Infrastructure Engineer

Job Requirements An Infrastructure Engineer works in complex development and migration of application projects to Azure cloud. You will work with business analysts, application developers, architects and data stakeholders to understand the customer business cases and build secure and scalable Azure environment

Key Accountabilities

• Understanding the requirement and individually handling the cloud environment with minimal guidance.
• Designing, building and Implementation of environment setup in Azure cloud for applications, data team and DevOps.
• Implementation of Azure cloud resources with security features enabled.
• Good co-ordination with project Architects, Developers, Data team and infrastructure support team for resolving infrastructure related issues.
• Ownership of documentation, tracking and prioritizing tasks and highlighting the foreseen blockers upfront.
• Ensure the azure cloud environment is as per compliance.

Key Experience And Qualifications

• Degree level education in Mathematics, Computing or Engineering discipline or equivalent experience.
• 8+ years of total experience with 5+ years in Azure Cloud (IaaS, PaaS, SaaS) in relation to data intensive solutions
• Cloud Services Experience
• Designing solutions and implementation/migration of data intensive applications to Azure Cloud.
• Design, configure and optimize data related service in Azure such as Databricks, Data Factory, Synapse, Data Lake, Database & Batch services.
• Ability to design/implement/Troubleshoot end-to-end pipelines in Data platform for related projects.
• Configuring App gateway, IaaS, AD, Firewall & Networking in the context of PaaS
• Implement SQL & NO SQL solutions in Azure Data platform.
• Experience is migrating data from On-prem to Cloud environment.
• Exposure to Cybersecurity standards and implementation of cloud and resource controls to meet standards
• DevOps
• Knowledge of Dev-Ops processes (including CI/CD) and Infrastructure as code is essential.
• Expert working on IaC tools such as Terraform, Biceps, ARM, PowerShell to automate deployment with Azure devops.
• Design and implement CI/CD pipelines in Azure Devops using YAML pipelines and scripts with best practice.
• Good understanding in Git, Repos, Artifacts, Branching strategy, Conflicts, Policies, Pipelines as applied to data solutions
• Desirable
• Knowledge in Kubernetes, Container technologies are added advantage.

Work Experience An Infrastructure Engineer works in complex development and migration of application projects to Azure cloud. You will work with business analysts, application developers, architects and data stakeholders to understand the customer business cases and build secure and scalable Azure environment

Key Experience And Qualifications

• Degree level education in Mathematics, Computing or Engineering discipline or equivalent experience.
• 8+ years of total experience with 5+ years in Azure Cloud (IaaS, PaaS, SaaS) in relation to data intensive solutions
• Cloud Services Experience
• Designing solutions and implementation/migration of data intensive applications to Azure Cloud.
• Design, configure and optimize data related service in Azure such as Databricks, Data Factory, Synapse, Data Lake, Database & Batch services.
• Ability to design/implement/Troubleshoot end-to-end pipelines in Data platform for related projects.
• Configuring App gateway, IaaS, AD, Firewall & Networking in the context of PaaS
• Implement SQL & NO SQL solutions in Azure Data platform.
• Experience is migrating data from On-prem to Cloud environment.
• Exposure to Cybersecurity standards and implementation of cloud and resource controls to meet standards
• DevOps
• Knowledge of Dev-Ops processes (including CI/CD) and Infrastructure as code is essential.
• Expert working on IaC tools such as Terraform, Biceps, ARM, PowerShell to automate deployment with Azure devops.
• Design and implement CI/CD pipelines in Azure Devops using YAML pipelines and scripts with best practice.
• Good understanding in Git, Repos, Artifacts, Branching strategy, Conflicts, Policies, Pipelines as applied to data solutions
• Desirable
• Knowledge in Kubernetes, Container technologies are added advantage.