Azure Data Platform Engineer

TL;DR

Azure Data Platform Engineer (Azure/Databricks): Designing and managing scalable cloud data platforms with an accent on migration strategy, infrastructure automation, and platform reliability. Focus on building robust CI/CD pipelines, implementing IaC with Terraform, and ensuring secure, high-performance data environments on Azure and Databricks.

Location: Must be based in the European Union region with a valid work permit

Company

A global AI-first digital transformation and engineering partner with over 25 years of experience, delivering data-driven solutions for enterprise clients.

What you will do

• Collaborate with architects and data engineers to design target-state data platform architectures.
• Manage cloud infrastructure using Terraform and IaC best practices.
• Deploy and maintain Kubernetes-based platform environments.
• Develop and maintain CI/CD pipelines for automated provisioning and operations.
• Implement security, governance, and identity management standards.
• Optimize platform reliability, scalability, and cost efficiency.

Requirements

• Must be based in the European Union region and hold a valid work permit.
• Strong hands-on experience with Microsoft Azure.
• Proficiency with Databricks and/or Microsoft Fabric.
• Extensive experience with Terraform and Infrastructure as Code.
• Hands-on experience with Kubernetes administration.
• Strong Python development skills for automation and tooling.
• Solid understanding of DevOps practices and CI/CD implementation.

Nice to have

• Experience with large-scale data platform modernization programs.
• Knowledge of dbt, Apache Airflow, or FinOps practices.
• Experience with observability, monitoring, and alerting platforms.
• Familiarity with data governance frameworks.

Culture & Benefits

• Focus on engineering excellence and continuous knowledge sharing.
• Consulting-oriented environment with exposure to diverse enterprise projects.
• Strong emphasis on professional growth and technical leadership.
• Collaborative culture working with global experts in AI and data.

Hiring process

• CV review
• HR call
• Technical interview
• Client interview
• Final decision