Cloud engineer Offres d'emploi - Pickering, ON

Role Azure Cloud Engineer

Location Address : 4100 Gordon Baker Rd, Scarborough, ON M1W 3E8 / Hybrid

Duration : Contract

Required Skills :

• CDKTF Expertise : Proficient with CDKTF and Terraform for Azure infrastructure
• Azure AI Services : Hands-on experience with Azure OpenAI, Cognitive Services, and Machine Learning
• Azure Data Services
• Azure Cosmos DB (SQL API, MongoDB API)
• Azure Data Factory (pipelines, data flows, integration runtime)
• Azure SQL Managed Instance and SQL Database
• Azure Synapse Analytics
• Azure Core Services : VNet, Storage, App Services, Key Vault, application config
• DevOps : CI / CD pipelines, Azure DevOps, GitHub Actions, Docker
• Programming : TypeScript / Python skills for infrastructure as code
• The overall skills are highlighted above that are a must and the below shows the day-2-day expectations in terms of experience :
• Infrastructure as Code Development
• Design, develop, and maintain infrastructure as code using CDKTF for Azure AI services, data platforms, and database solutions
• Implement automated deployment pipelines for AI and data infrastructure
• Create reusable CDKTF constructs and modules for data and AI service patterns
• Manage version control and CI / CD for infrastructure code using Azure DevOps or GitHub Action
• Azure AI Services Implementation
• Provision and configure Azure AI services including :
• Azure OpenAI Service and large language models
• Azure Cognitive Services (Vision, Speech, Language, Decision)
• Azure Machine Learning Workspace and MLOps pipelines
• Document intelligence
• Azure Cognitive Search
• Implement MLOps practices for machine learning model deployment and management
• Configure AI service networking, security, and compliance
• Data Platform Management
• Azure Cosmos DB : Design and implement globally distributed NoSQL databases
• Configure multi-region replication and consistency levels
• Implement partitioning strategies and optimize query performance
• Set up automatic scaling and monitoring
• Azure Data Factory : Build and manage ETL / ELT pipelines
• Design data integration workflows and data movement patterns
• Implement data transformation activities and data flows
• Configure triggers, monitoring, and error handling
• Azure SQL Managed Instance : Deploy and manage enterprise-grade SQL databases
• Configure high availability and disaster recovery
• Implement security features including TDE, Always Encrypted
• Manage performance tuning and maintenance tasks
• Cloud Infrastructure Management
• Design and implement secure, scalable Azure infrastructure for data and AI workloads
• Configure virtual networks, private endpoints, and network security groups
• Implement monitoring with Azure Monitor, Log Analytics, and Application Insights
• Manage identity and access management (Azure AD, RBAC, managed identities)
• Database & Data Engineering Skills
• Cosmos DB partitioning, indexing, and performance optimization
• Data Factory pipeline design and orchestration
• SQL Managed Instance migration and management
• Data modeling for both relational and NoSQL databases
• Data security and compliance implementation.