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.