Cloud/DevOps Engineer

About the Role:

Were seeking a skilled Cloud/DevOps Engineer with a strong focus on platform automation observability and hardening to support the Data Analytics Platform team. We are supporting a business unit of one of the biggest global furniture companies in the world to build a data & analytics platform.

In this new role you will play a crucial part in developing and optimizing the D&A platform. This is a hands-on role requiring expertise in Azure Python automation and infrastructure as code (IaC) allowing dynamic scaling and provisioning for efficient data pipeline operations.

Key Responsibilities:

• Create and maintain Infrastructure as code using Terraform (must) for Data & analytics workloads

• Build and Manage Github Actions pipelines for CI/CD and Release Management workflows.

• Manage Github repos and automation.

• Implement security architecture to ensure data security .

• Implement observability patterns using Azure Monitor Azure Application Insights and Log Analytics Workspace.

• Develop Python functions classes & packages

• Design and build reusable components frameworks and libraries at scale to support analytics products (Python Spark SQL)

• Implement automated testing for the Data & Analytics platform

• Support in building Data & Analytics Accelerators

• Define and implement the configuration of Azure PAAS and IAAS services

Key Requirements:

• Experience: 4 years in Data Engineering Software Engineering or DevOps.

• Technical Skills:

  • Strong proficiency in at least one programming language relevant to data operations (Python Terraform).

  • Extensive experience with cloud environments (Azure; GCP experience is a plus).

  • Proficiency in CSD tools (Azure DevOps GitHub).

  • Hands-on experience with Databricks for data operations.

• Platform-Focused Mindset: Skilled in building resilient automated platforms distinct from core data engineering roles.

• Automation Expertise: Proven track record in automation within cloud environments including dynamic provisioning and scaling of data pipelines.

• Observability & Reliability: Experience designing systems for monitoring troubleshooting and maintaining service uptime.

• Hybrid Work Model: Ability to work from the Leiden office minimum 2-3 days per week.

Additional Information:

This role offers flexibility with the potential to work four days a week though five days are preferred. You will be working within a dynamic team that values innovation collaboration and proactive problem-solving helping to shape our clients Data Analytics Platform.

If you are a Cloud/DevOps Engineer passionate about platform automation data operations and cloud architecture apply!