As a Senior Cloud / Platform Engineer, you will hands-on build, automate, and maintain an Azure cloud platform with a focus on data, analytics, and applications. The platform continuously evolves with some mature components and others in early design stages. There is a clear technical vision and room to define the implementation of a standardized, maintainable platform.
You will support engineering teams including Data Engineers, Analytics Engineers, AI/ML Engineers, and Software Engineers deploying and operating their solutions securely, reliably, and efficiently by providing reusable infrastructure, automation, and platform standards. Technologies involved include Databricks, Unity Catalog, MLflow, Azure Data Factory, containerized environments on AKS, Postgres, among others.
Must-have skills:
- Azure Cloud: strong hands-on experience with Azure infrastructure and cloud services.
- Terraform: Infrastructure as Code experience with reusable modules and lifecycle management.
- Git: solid understanding of version control, branching, pull requests, and code reviews.
- CI/CD pipelines: experience designing, implementing, and troubleshooting automated deployment.
- Azure Databricks: deep knowledge of architecture, workspace admin, access management, compute, networking, and automation. Ability to independently troubleshoot platform issues and advise on architecture.
- Problem-solving: strong troubleshooting and independent investigation of complex technical issues.
- English proficiency: strong written and verbal communication skills.
Additional valuable knowledge includes Azure networking, Microsoft Entra ID, containers and Kubernetes, data platform engineering, and monitoring tools.
Key responsibilities include designing and maintaining Azure infrastructure using Terraform, improving CI/CD pipelines, building reusable infrastructure components, enhancing platform observability, and collaborating with engineering teams.
We value quality over quantity, simplicity, automation-first mindset, ownership, critical thinking, technical depth, collaboration, and continuous improvement. The ideal candidate has strong fundamentals in Azure, Databricks, Terraform, and CI/CD along with deeper expertise in areas like networking, automation, Kubernetes, or observability.