We are looking for a Data Platform Engineer with strong Azure and IaC skills to help us build, automate, and operate our cloud-based Data Platform (centered around Databricks).

You might be our missing piece if you have:

• Deep understanding of Azure services, including resource management, networking, and security.
• Hands-on experience with Infrastructure as Code (Terraform) and module development.
• Practical experience with Azure DevOps (Git repos, YAML pipelines, CI/CD automation).
• Strong scripting skills in Bash (PowerShell is a plus).
• Proficiency in Python with the ability to write clean, efficient, and reusable code for data processing and transformation.
• Ability to troubleshoot environment and deployment issues across Azure components.
• A proactive, ownership-driven mindset and the ability to communicate design choices clearly (e.g., using ADRs).

We would be thrilled if you have:

• Experience with Azure Databricks, Azure Data Factory, or other data analytics services.
• Background or exposure to Data Engineering (Delta Lake, ETL/ELT, streaming pipelines).
• Knowledge of Azure cost management, FinOps principles, and cost optimization techniques.
• Familiarity with cloud architecture principles such as the Azure Cloud Adoption Framework and the Well-Architected Framework.
• Experience with platform observability, monitoring, and operational excellence practices.

We will be working together on:

• Building and maintaining the automation backbone of our Data Platform using Terraform and Azure DevOps.
• Operating and improving the Azure-based analytics ecosystem (Databricks, Data Factory, storage, networking).
• Designing, implementing, and automating CI/CD pipelines for our data workloads and platform components.
• Ensuring the platform adheres to security, governance, and compliance standards.
• Optimizing cloud resource usage and helping guide FinOps-aligned decisions.
• Collaborating with Data Engineers, Architects, and business teams to deliver high-quality, scalable data solutions.
• Participating in code reviews, documentation efforts, and cross-team architecture discussions.

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