Cloud Jobs in Markham, ON
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Cloud • markham on
Azure Cloud Engineer
VDart IncScarborough, ON, CanadaCloud Security Architect
Recrute ActionMarkham, Ontario, Canadacloud architect
Trident Consulting IncRichmond Hill, ON, CA- New!
Principal Cloud Applications Administrator
OpenTextRichmond Hill, York Region, CACloud Security Architect
Recutify Inc.Markham, Ontario, CanadaEngineer - Cloud AI Infrastructure
Huawei CanadaMarkham, York Region, CACloud Engineer Manager
Onico SolutionsRichmond Hill, York Region, CAEngineer - Cloud AI Infrastructure
HuaweiMarkham, York Region, CAKubernetes Cloud Infra Production Engineer
IBMMarkham, York Region, CASenior Cloud Security Engineer
Saint ElizabethMarkham, York Region, CAAzure Cloud Apps Developer
Pet ValuMarkham, York Region, CACloud Services Program Manager
NLB ServicesRichmond Hill, York Region, CA- Promoted
Senior Azure Cloud Engineer
Venture Computers of Canada Inc.Markham, ON, CanadaSenior Cloud Security Engineer
SE HealthMarkham, York Region, CAEngineer - Cloud AI Infrastructure
Huawei Technologies Canada Co., Ltd.Markham, York Region, CACloud Engineer
The Nationwide GroupMarkham, York Region, CACloud Design Architect
EmersonRichmond Hill, Ontario, CanadaSenior Azure Cloud Engineer
Xplore.Markham, Ontario, Canada- Brossard, QC (from $ 77,476 to $ 233,375 year)
- Niagara Falls, ON (from $ 124,316 to $ 192,095 year)
- Sainte-Therese, QC (from $ 91,691 to $ 187,805 year)
- Calgary, AB (from $ 93,707 to $ 185,250 year)
- Fredericton, NB (from $ 101,048 to $ 182,832 year)
- Sault Ste. Marie, ON (from $ 74,796 to $ 176,245 year)
- Chatham-Kent, ON (from $ 85,898 to $ 174,642 year)
- Ajax, ON (from $ 100,000 to $ 172,914 year)
- Coquitlam, BC (from $ 108,125 to $ 172,320 year)
- Markham, ON (from $ 91,525 to $ 169,583 year)
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Azure Cloud Engineer
VDart IncScarborough, ON, Canada- Full-time
- Quick Apply
Job Title : Azure Cloud Engineer
Location : Scarborough, ON
Duration : Contract
Job Summary :
We are seeking an experienced Cloud Azure Engineer with strong expertise in CI / CD pipeline automation, application development, and a solid understanding of AI / ML integration within cloud environments.
The ideal candidate will design, implement, and manage scalable Azure cloud solutions, ensuring seamless deployment and operational excellence while enabling AI-driven innovations.
Key Responsibilities :
Cloud Infrastructure & Deployment
Design, implement, and maintain Azure cloud infrastructure using best practices for scalability, security, and cost optimization.
Automate provisioning and configuration using Azure DevOps, Terraform, or ARM templates.
CI / CD Pipeline Management :
Build, maintain, and optimize CI / CD pipelines for seamless integration and delivery across environments.
Implement continuous testing, monitoring, and deployment using Azure DevOps, GitHub Actions, or Jenkins.
Ensure smooth code deployments and rollback mechanisms with version control (Git).
Coding & Development :
Develop and maintain scripts, automation tools, and integrations using Python, PowerShell, or C#.
Collaborate with developers to containerize and deploy applications using Docker and Kubernetes (AKS).
AI & Data Integration :
Support integration of AI / ML models into cloud-based applications using Azure Machine Learning, Cognitive Services, or OpenAI Service.
Work closely with data and AI teams to enable secure model deployment and monitoring in production.
Monitoring & Security :
Implement monitoring, alerting, and performance optimization using Azure Monitor, Log Analytics, and Application Insights.
Ensure compliance with security standards, manage access control, and enforce DevSecOps best practices.
Required Skills & Qualifications :
Bachelor's degree in Computer Science, Engineering, or related field.
6+ to 9 years of experience in Azure Cloud Engineering or related roles.
Hands-on experience with Azure DevOps, CI / CD pipelines, and Infrastructure as Code (IaC).
Strong scripting / coding skills in Python, PowerShell, or C#.
Familiarity with Docker, Kubernetes, and microservices architecture.
Understanding of AI / ML workflows and tools (Azure ML, Cognitive Services, APIs).
Experience with monitoring, logging, and troubleshooting in cloud environments.
Preferred Qualifications :
Azure certifications (e.g., AZ-104, AZ-204, or AZ-400).
Experience integrating AI models into production environments.
Exposure to GitOps and DevSecOps methodologies.
Knowledge of REST APIs, event-driven architectures, and serverless computing (Azure Functions, Logic Apps).
Soft Skills :
Strong analytical and problem-solving skills.
Excellent communication and collaboration abilities.
Ability to work in an agile, fast-paced environment.