Azure Infrastructure(L2) Engineer - Unified Data Platform

Job Summary: We are seeking an Azure Infrastructure Engineer to design, implement, and maintain the core cloud architecture for our unified data platform on Microsoft Azure. The ideal candidate will have extensive hands-on experience in Infrastructure as Code (IaC), enterprise networking, and cloud security to provide a stable, secure, and automated foundation for our enterprise-wide data and analytics initiatives.
Key Responsibilities:

Architect and Provision Data Infrastructure: Design and deploy the underlying Azure infrastructure for data services including Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage (ADLS Gen2), and Databricks workspaces using a modular, reusable approach.
Automated Environment Management: Build and maintain Terraform configurations to automate the lifecycle of the data platform across Development, Staging, and Production environments. Manage Terraform state files securely using Azure Storage with state locking.
Network & Connectivity Design: Implement enterprise networking solutions including hub-and-spoke topology, Virtual WAN, and Azure Firewall. Ensure all data assets are isolated using Private Endpoints, VNets, and Network Security Groups (NSGs).
Platform Security & Governance: Manage Azure Active Directory (Entra ID), implementation of RBAC, and data security policies. Configure encryption-at-rest/transit and manage secrets using Azure Key Vault.
AI & ML Infrastructure Support: Provision and harden Azure Machine Learning workspaces and compute clusters. Implement the infrastructure requirements for Azure OpenAI service integrations, focusing on private connectivity and quota management.
DevSecOps Integration: Collaborate with data teams to support CI/CD pipelines using Azure DevOps. Implement pipelines/workflows for infrastructure changes, including pull request reviews and automated testing gates.
Observability & Monitoring: Monitor the health of the infrastructure using Azure Monitor and Log Analytics. Set up alerts for platform availability, connectivity issues, and resource performance.
L2/L3 Infrastructure Escalation: Troubleshoot and resolve complex escalations related to networking bottlenecks, service-level failures, and IAM permission conflicts within the data platform.
Cost Management & FinOps: Optimize cloud costs by analysing resource utilization (e.g., Databricks clusters, Synapse pools) and implementing autoscaling, right-sizing, and shutdown schedules.
Business Continuity: Design and implement backup, disaster recovery, and high-availability strategies for critical infrastructure components and storage accounts.
Documentation: Maintain comprehensive documentation for platform architecture, infrastructure diagrams, runbooks, and disaster recovery procedures.

Required Qualifications:

3+ years of experience working with Microsoft Azure cloud services, with a specific focus on platform engineering and infrastructure automation, preferably in Singapore Government project(GCC).
Expert-level Infrastructure as Code (IaC): Deep hands-on experience with Terraform, ARM templates, or Bicep for managing complex cloud environments.
Advanced Networking Knowledge: Proficiency in designing secure environments using Private Links, Hub-and-Spoke models, and Azure Firewall.
Platform Experience: Strong experience in provisioning Azure Synapse, Data Factory, Azure Data Lake, Azure Foundry and AzureML workspaces.
Automation & Scripting: Proficiency in PowerShell, Azure CLI, or Python for infrastructure automation and management tasks.
DevOps Tooling: Experience building and maintaining CI/CD pipelines in Azure DevOps.
Certifications: Microsoft Azure certifications such as AZ-305 (Azure Solutions Architect Expert) or AZ-104 (Azure Administrator) are required. Terraform Associate certification is highly preferred.
Troubleshooting: Strong skills in performance tuning and root cause analysis for infrastructure-level issues.

Preferred Skills:

Security & Compliance: Knowledge of security best practices (CIS benchmarks) and compliance frameworks (IM8) relevant to data platforms and infra in Government on Commercial Cloud(GCC).
Containerization: Experience with Docker and Azure Kubernetes Service (AKS) as it relates to hosting ML or data workloads.
Modern Data Architecture: Familiarity with the infrastructure requirements of Medallion and Lakehouse architectures.
AI/LLM Infrastructure: Understanding of the resource and networking requirements for scaling Azure OpenAI and generative AI applications.

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Azure Cloud Engineer