Back
Mid-level, metro cloud role with popular title and broad skills, high applicant competition.
Cloud platform skills transferable across industries but Databricks specialization increases domain specificity.
Explicit years, mandatory Databricks and Azure platform skills, and IaC requirements make filters stringent.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own the engineering, configuration, and operation of Azure Databricks workspaces and related Azure services to ensure production-grade, reliable data pipelines and platform operations.
Deliver automation using infrastructure-as-code (Terraform/Bicep) and CI/CD for Databricks and supporting Azure resources to enhance deployment efficiency and platform reliability.
Collaborate closely with Data Science & AI teams and Cloud Operations to support AI delivery, implement security/compliance controls, and improve monitoring, cost management, and operational incident response.
5+ years of cloud/platform engineering experience, preferably on Azure; Work Experience Required: 5+ years cloud/platform engineering with 2+ years hands-on Azure Databricks experience.
Strong hands-on expertise in Azure Databricks platform engineering including troubleshooting workspace, networking, and performance issues.
Proficient with automation, CI/CD, IaC tools (Terraform, ARM/Bicep), and Azure DevOps or GitHub for pipeline deployments.
Experience with Azure networking and security patterns including VNETs, private endpoints, Key Vault, managed identities, and implementation of least-privilege access and audit controls.
Experienced in operating enterprise-scale Azure Databricks platforms for data and AI workloads with focus on reliability, security, and cost-efficiency.
Skilled in translating data science and AI team needs into actionable platform engineering work while collaborating across distributed, cross-functional teams in hybrid settings.
Demonstrates a delivery and operational mindset, thriving in troubleshooting, hardening pipelines, automating deployments, and maintaining production reliability.