Cloud Engineer

Talent; Canberra; Hybrid; AUD 120,000 - 160,000; Full time

Job summary

Talent in Canberra is seeking a Senior Azure Cloud Platform Infrastructure Engineer to design, build and maintain Azure-based infrastructure for data and analytics workloads in a large government environment.

You will implement IaC with Terraform, develop Azure DevOps pipelines, and apply security controls across IAM, networking and policy, collaborating with multidisciplinary teams in an Agile delivery process.

Qualifications

• Strong experience designing and maintaining cloud IaaS, PaaS, SaaS platforms.
• IaC approach for cloud infra with Terraform.
• Hands-on Azure engineering with security best practices.

Responsibilities

• Design, build and maintain Azure-hosted infrastructure for data and analytics workloads.
• Develop and implement cloud infra using Terraform IaC.
• Build and support Azure DevOps CI/CD pipelines for infra deployment.
• Work with Azure data services like Databricks, Data Factory, Web Apps, Logic Apps.
• Apply Azure security controls across IAM, networking and policy.
• Collaborate with stakeholders to gather requirements for analytics/AI solutions.
• Support Databricks, Microsoft Fabric and other analytics services.
• Work in multidisciplinary Agile teams.

Skills

Azure

Terraform

Azure DevOps

IAM

Security

Databricks

Microsoft Fabric

MLOps

LLMOps

Data Lakes

Geospatial data

Agile

NV1 clearance

Azure data services

Tools

Job description

Job Description

• Canberra, ACT | Hybrid working arrangements
• 12-month contract | 2 x extension options
• Security clearance: NV1 clearance required

Position Overview

An opportunity is available for Senior Azure Cloud Platform Infrastructure Engineers to deliver cloud infrastructure supporting enterprise data, analytics and advanced technology workloads within a large Australian Government environment.

Working as part of a multidisciplinary team, you will take responsibility for the detailed solution design, development and implementation of Azure infrastructure, with a strong focus on Infrastructure as Code using Terraform. The role will suit an experienced Azure engineer who can combine hands-on cloud engineering with strong security practices and collaborate effectively with stakeholders to deliver scalable data and analytics solutions.

Key Duties

• Design, build and maintain Azure-hosted infrastructure supporting data and analytics workloads.
• Develop and implement cloud infrastructure using Terraform-based Infrastructure as Code (IaC).
• Build and support Azure DevOps CI/CD pipelines for infrastructure deployment.
• Work across Azure data and analytics services including Azure Databricks, Azure Data Factory, Azure Web Apps and Logic Apps.
• Apply Azure security controls across networking, Identity and Access Management (IAM) and policy.
• Collaborate with stakeholders to gather requirements and design and implement advanced analytics and AI solutions.
• Support the delivery and administration of Databricks, Microsoft Fabric and other analytical services.
• Work collaboratively within multidisciplinary teams using Agile delivery methodologies.

Skills and Experience Required

• Strong experience designing, building and maintaining cloud-hosted IaaS, PaaS and SaaS platforms and services.
• Demonstrated experience developing, implementing and supporting cloud infrastructure using an Infrastructure as Code approach.
• Strong hands-on experience with Microsoft Azure and Terraform.
• Experience with Azure DevOps and CI/CD pipelines.
• Sound understanding of cloud security, particularly IAM, networking and policy.
• Experience delivering projects within data and analytics environments, including data engineering, storage or data science.
• Experience working effectively in multidisciplinary Agile teams.
• Experience delivering or administering Databricks, Microsoft Fabric or similar analytical services.
• Ability to obtain a Negative Vetting Level 1 (NV1) security clearance.
• Machine Learning Operations (MLOps) and Large Language Model Operations (LLMOps).
• Traditional data technology solutions.
• Data Lake environments.
• Geospatial platforms.