Cloud Engineer

Jobgether; New Zealand; On-site; NZD 90,000 - 140,000; Full time

Job summary

Jobgether is seeking a Cloud Engineer in New Zealand to join a partner-led technical team. You will onboard application teams to Databricks, build Data Landing Zones, and work with Azure resources, IaC, automation, and deployment pipelines.

As a first-line technical point of contact, you will troubleshoot, document procedures, and identify opportunities to automate. The role blends hands-on cloud engineering with application support to improve data platform operations and enable scalable cloud

Qualifications

• 1–3 years of hands-on experience with Databricks in a technical or operational environment.
• 1–3 years of experience with Azure Data Factory.
• Experience in application support, technical operations, cloud support, or a similar role.
• Familiarity with Azure, with exposure to AWS or GCP considered an advantage.
• Experience with source-control systems such as Git, GitHub, or GitLab.
• Understanding of Unity Catalog, RBAC and Delta Sharing is desirable.
• Experience with IaC tools such as Terraform, Bicep, or AWS CDK.
• Experience with CI/CD pipelines and automation platforms (Azure DevOps, Jenkins, GitHub Actions).
• Scripting or development with Python, PowerShell, Bash, or similar.

Responsibilities

• Provide first-level technical support to application teams via ServiceNow, resolving Databricks and cloud requests.
• Gather, clarify, and analyze requirements for onboarding new Data Landing Zones (DLZs).
• Execute pipelines, scripts, and automated processes to provision Azure and Databricks resources.
• Support deployment of Azure resources using IaC practices.
• Identify repetitive activities and develop automation to improve efficiency and response times.
• Collaborate with cross-functional teams to resolve issues and ensure smooth onboarding.
• Create and maintain documentation covering support procedures and workflows.
• Contribute to the ongoing improvement of cloud support operations and the Databricks environment.

Skills

Databricks

Azure cloud

Infrastructure as Code

CI/CD pipelines

Python scripting

PowerShell

Shell scripting

Git workflows

Terraform

Azure DevOps

Jenkins

GitHub Actions

Tools

Git

GitHub

GitLab

Terraform

Bicep

AWS CDK

Azure DevOps

Jenkins

GitHub Actions

Databricks

Unity Catalog RBAC

Delta Sharing

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Cloud Engineer based in New Zealand.

Join a technical team focused on supporting and scaling modern cloud-based data environments.
In this role, you will help application teams onboard to Databricks and build reliable Data Landing Zones (DLZ).
You will work with Azure resources, Infrastructure as Code, automation, and deployment pipelines to deliver efficient solutions.
As a first-line technical point of contact, you will troubleshoot requests and help resolve issues through structured support processes.
You will also identify opportunities to automate repetitive activities and continuously improve operational workflows.
The role combines hands-on cloud engineering with application support in a collaborative, cross-functional environment.
It is an excellent opportunity to deepen your expertise in Databricks, Azure, IaC, and cloud automation while making a direct impact on data platform operations.

Accountabilities

• Provide first-level technical support to application teams through the ServiceNow ticketing system, investigating and resolving common Databricks and cloud-related requests.
• Gather, clarify, and analyze technical requirements for onboarding new Data Landing Zones (DLZs).
• Execute pipelines, scripts, and automated processes to provision, configure, or modify Azure and Databricks resources.
• Support the deployment of commonly requested Azure resources using Infrastructure as Code (IaC) practices.
• Identify repetitive manual activities and develop automation to improve efficiency, consistency, and support response times.
• Collaborate with application, cloud, data, and other cross-functional teams to resolve technical issues and ensure smooth onboarding.
• Create, maintain, and continuously improve documentation covering support procedures, workflows, configurations, and troubleshooting processes.
• Contribute to the continuous improvement of cloud support operations and the overall Databricks environment.

Requirements:

• 1–3 years of hands-on experience working with Databricks in a technical or operational environment.
• 1–3 years of experience with Azure Data Factory.
• Previous experience in application support, technical operations, cloud support, or a similar role.
• Familiarity with major cloud platforms, particularly Azure, with exposure to AWS or GCP considered an advantage.
• Experience using source-control systems such as Git, GitHub, or GitLab.
• Understanding of Databricks capabilities such as Unity Catalog, role-based access control (RBAC), authentication mechanisms, and Delta Sharing is highly desirable.
• Experience working within the Azure ecosystem and understanding of cloud resource management.
• Familiarity with Infrastructure as Code tools such as Terraform, Bicep, or AWS CDK.
• Experience with CI/CD pipelines and automation platforms such as Azure DevOps, Jenkins, or GitHub Actions is a plus.
• Scripting or development experience with Python, PowerShell, Bash, or similar technologies.
• Strong analytical and troubleshooting abilities, combined with attention to detail and a proactive approach to problem-solving.
• Ability to communicate clearly with application teams and collaborate effectively across technical and non-technical stakeholders.

Benefits:

• Opportunity to work hands-on with Databricks, Azure, cloud infrastructure, and modern data technologies.
• Exposure to Infrastructure as Code, CI/CD, automation, and cloud platform operations.
• Collaborative environment with opportunities to work closely with application and cross-functional technical teams.
• Opportunity to develop expertise in a growing data and cloud technology ecosystem.
• Role combining technical support, cloud engineering, automation, and continuous improvement.
• Potential for professional growth through exposure to a broad range of cloud and data platform challenges.