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Leading Insurer is seeking a Senior Data Platform Engineer to own and scale the cloud data infrastructure that underpins analytics, ML, and Data as a Service across its network.
You will automate deployments with Terraform/Ansible, build CI/CD pipelines, manage Dockerized services on AKS, and implement security for 24x7 operations. A CS/IT degree and 3+ years in Cloud Infrastructure or DevOps with Azure are required.
About the Client: Our client is a massive, well-backed enterprise organization with a complex, high-volume technology environment. They are actively expanding a centralized enterprise data capability designed to support advanced analytics, machine learning, and Data as a Service (DaaS) across their entire business network.
The Role & Landscape: You will step in to own the underlying cloud infrastructure that keeps their data platform running. You aren't just watching dashboards; you are actively automating deployments, hardening security, and ensuring massive datasets move efficiently.
Manage and scale Azure cloud infrastructure supporting heavy data engineering workloads.
Write and maintain Infrastructure as Code (IaC) using Terraform and Ansible to automate resource provisioning.
Build and optimize CI/CD pipelines (Jenkins, Azure DevOps, Git) to reduce manual deployment overhead.
Maintain containerized environments using Docker and AKS.
Handle ongoing platform monitoring, security configurations (access controls, encryption), and 24x7 operational troubleshooting.
What We Are Looking For:
A solid technical foundation with a degree in Computer Science or IT.
At least 3 years of commercial experience specifically focused on Cloud Infrastructure or DevOps, with Azure being your strongest platform.
Hands-on, daily experience using IaC tools (Terraform, Ansible, etc.) and building CI/CD pipelines.
Competence with containerization (Docker, AKS/EKS).
Solid communication skills in both Chinese and English to effectively navigate an enterprise matrix.
Bonus: If you have previously supported big data stacks (Databricks, Kafka, Spark) or worked in the insurance industry, we definitely want to talk to you.