Job title: Platform Engineer - PropertyiQ
Job type: Permanent
Emp type: Full-time
Location: Sydney CBD
Job published: 14-10-2026
Job ID: 73500

Job Description

 
As a Platform Engineer, you will own the engineering foundations that every other development team builds on—from how we deploy and operate our services, to how we detect and respond to problems, to the tooling that makes all of it repeatable. You will stand up and automate environments end-to-end, build the automation that moves us forward as we evolve our platform, and own the frameworks that keep every release trustworthy. You will be the engineer other teams rely on when something foundational needs to just work.

What you offer

  • Cloud Platform & Kubernetes Expertise: Strong hands-on experience managing and scaling cloud infrastructure on Google Cloud Platform (GCP) and orchestrating containerized workloads utilizing Kubernetes (GKE).
  • Platform Automation & Ownership: Proven capability to design, build, and maintain automation for standing up GCP and Kubernetes environments end-to-end, actively reducing manual toil and driving operational efficiency across development teams.
  • CI/CD & Delivery Engineering: Hands-on expertise building and hardening secure, automated CI/CD pipelines (e.g., GitHub Actions, GitLab CI/CD) to ensure rapid, reliable, and repeatable deployments of containerized services.
  • Platform Reliability & Observability: Practical experience building robust monitoring, alerting, and logging into GCP/Kubernetes environments from the ground up, leading structured incident response, and driving continuous improvement in operational maturity.
  • Migration & Data Automation: Experience designing and implementing automated tooling to streamline system and data migrations, ensuring legacy workloads are transitioned to modern containerized platforms with minimal risk and manual intervention.
  • Integration Engineering: Strong background integrating core systems and platform components—including API gateways, service meshes, event-driven architectures, and messaging queues—to enable highly reliable, decoupled architectures.
  • AI-Assisted Engineering: Comfort operating in an AI-assisted engineering environment, leveraging modern tools (e.g., Claude, GitHub Copilot) to accelerate delivery speed while maintaining a strict focus on quality, security, and design standards.
  • Collaborative Problem-Solving: Demonstrated ability to break down ambiguous, multi-system problems and solve them systematically in close, cross-functional collaboration with the wider engineering organization.
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