Mid-Senior Cloud Engineer Azure

At wemetrix, we’re reshaping how enterprises manage credit risk, financial operations and up-sell opportunities through our flagship platform, VALUEBOARD®. We combine deep domain expertise with state-of-the-art technology to help finance leaders make smarter, faster decisions. 

As a tech-first company, we value clarity, ownership, and trust, and we’re building a culture where engineers are empowered to deliver impactful work, grow in their craft, and feel proud of what they ship. 

Join us as we scale our platform, our cloud services, and our team. 

We’re looking for a Mid-Senior Cloud Engineer who will own the design and implementation of cloud infrastructure powering VALUEBOARD®. You’ll be the go-to person for deploying and optimizing Azure services, managing environments across staging and production, and shaping our DevOps and cloud strategy alongside engineering and data teams. 

• →Design, provision, and manage Azure infrastructure using IaC tools (Terraform or Bicep) 

• →Deploy and maintain cloud services including Databricks, AKS, Data Factory, ADX, and Blob Storage 

• →Automate CI/CD pipelines for data services, ML model deployments, and platform components 

• →Implement monitoring, logging, and security best practices across environments 

• →Work with engineering, data, and ML teams to ensure reliable, scalable, and cost-effective cloud infrastructure 

• →Champion DevOps culture and continuously improve our tooling and operations 

• 4+ years of hands-on experience as a Cloud or DevOps Engineer (preferably on Azure) 

• Strong expertise with Azure core services (networking, compute, storage, identity) 

• Proficiency in Infrastructure as Code (Terraform, Bicep, or ARM templates) 

• Experience with CI/CD (Azure DevOps, GitHub Actions, or similar) 

• Solid scripting in PowerShell, Python, or Bash 

• Knowledge of containerization and orchestration (Docker, Kubernetes/AKS) 

• Security mindset and familiarity with RBAC, managed identities, and secrets management 

• Fluent in English (written and spoken) 

• Experience with MLOps tools (MLflow, model serving) 

• Exposure to Azure Data Explorer or ClickHouse 

• Microsoft Certifications (AZ-104, DP-203, AZ-400)