DevOps & FinOps Engineer – Azure Data Platform

About the role

We are seeking a DevOps/FinOps Engineer to own the reliability and cost efficiency of our Azure‑based data platform. You will work closely with data engineers and architects to implement automation, optimise spend and ensure the platform runs smoothly.

Key responsibilities

• Reduce technical debt in infrastructure and deployment tooling while promoting automation.
• Support incident response, root‑cause analysis and platform reliability monitoring.
• Implement cost‑optimisation measures such as cluster right‑sizing, storage tier changes, scheduling adjustments and pipeline restructuring.
• Contribute to capacity planning and cloud budget forecasting with the IT Management Team.
• Analyse cost drivers, propose concrete optimisation options and maintain tagging and charge‑back models.
• Build and maintain observability – monitoring dashboards, alerts and SLA tracking for the data platform.
• Support the Databricks migration by provisioning and deploying the new platform through repeatable automated processes.
• Continuously monitor platform costs, detect anomalies and attribute spend to workloads.
• Develop and maintain Infrastructure as Code for all data platform components on Azure.
• Design and maintain CI/CD pipelines for infrastructure provisioning, environment promotion and deployment automation.

Required profile

• Strong written and verbal communication skills, able to present cost and infrastructure trade‑offs to technical and non‑technical audiences.
• Continuous‑improvement mindset with a focus on automation and shared ownership of cloud spend.
• Experience in cloud cost analysis, tagging strategies and building charge‑back or show‑back models.
• Proven ability to evaluate and discuss cost‑optimisation alternatives with clear trade‑off analysis.
• Collaboration skills for working with external partners and internal stakeholders.

Required skills

• Hands‑on experience with Infrastructure as Code (Terraform or Bicep).
• Proficiency with Azure services, especially Azure Monitor and Log Analytics.
• Scripting in Python or Bash for automation.
• Experience with Databricks on Azure – cluster management, job scheduling and cost optimisation.
• Design and maintenance of CI/CD pipelines for cloud infrastructure.
• Knowledge of cloud cost optimisation techniques and tagging strategies.