Azure AI & Data Platform Engineer

Total Experience: 6–8 Years

Required Skill Set

1. Develop and maintain Infrastructure as Code (IaC) using CDKTF for Azure AI, data, and database workloads.
   

2. Build reusable CDKTF constructs and modules for standardized AI and data infrastructure patterns.
   

3. Implement automated CI/CD pipelines for IaC using Azure DevOps or GitHub Actions.
   

4. Manage version control, branching, and deployment workflows for infrastructure code.
   

5. Provision and configure Azure OpenAI Service, including deployment of large language models.
   

6. Implement and manage Azure Cognitive Services (Vision, Speech, Language, Decision).
   

7. Deploy and maintain Azure Machine Learning Workspaces and implement MLOps pipelines.
   

8. Configure and manage Document Intelligence and Azure Cognitive Search solutions.
   

9. Design globally distributed Azure Cosmos DB solutions (SQL API, MongoDB API).
   

10. Configure Cosmos DB multi-regional replication, partitioning, consistency policies, and performance tuning.
    

11. Build and manage Azure Data Factory ETL/ELT pipelines, data flows, triggers, and monitoring.
    

12. Deploy and administer Azure SQL Managed Instance and Azure SQL Databases, including HADR.
    

13. Implement SQL security features such as TDE, Always Encrypted, and access control.
    

14. Design and implement secure Azure infrastructure VNets, subnets, NSGs, private endpoints.
    

15. Configure Azure Storage, Key Vault, App Services, and Application Configuration services.
    

16. Implement cloud monitoring using Azure Monitor, Log Analytics, and Application Insights.
    

17. Manage IAM using Azure AD, RBAC, and managed identities for secure access.
    

18. Optimize data modeling for relational and NoSQL architectures.
    

19. Apply data governance, compliance, and security best practices across AI and data services.
    

20. Use strong TypeScript and Python skills for IaC automation, scripting, and tooling.