Databricks Platform Adminitrator

Key Responsibilities

• Platform Operations: Administer Databricks workspaces, including user provisioning, cluster governance, workspace configuration, job orchestration, and usage policy enforcement.
• AI/ML Enablement: Support MLflow, MLOps pipelines, and Mosaic AI for experimentation, deployment, and observability.
• Resilience & Availability: Design and implement disaster recovery and high availability strategies, including multi-region backups and failover planning.
• Infrastructure Automation: Automate provisioning and lifecycle management using Terraform and Python.
• Access & Security Governance: Manage access control via Unity Catalog, SCIM-based identity management, and workspace isolation with audit readiness.
• Performance & Cost Optimization: Monitor platform usage, enforce cluster policies, and optimize job and resource performance.
• Standardization: Establish reusable patterns, runbooks, cluster templates, and ML lifecycle standards.
• User Support & Enablement: Provide onboarding and operational support to data engineering, data science, and analytics teams.
• Feature Rollouts: Lead adoption of new features (e.g., Mosaic AI, Unity Catalog, Delta Live Tables) with documentation and change control.
• Training & Evangelism: Deliver training and promote responsible platform usage with a focus on automation and reliability.

Required Qualifications

• 10+ years in cloud infrastructure, platform operations, or data platform administration roles.
• Proven experience managing Databricks or similar cloud data platforms at scale.
• Experience administering or architecting data lake/lakehouse environments.
• Strong cross-functional communication and collaboration skills.
• Focus on platform stability, automation, and enablement of data/ML workflows.

Technical Expertise

• Databricks Platform: Unity Catalog, MLflow, Mosaic AI, Delta Live Tables, workspace management.
• Disaster Recovery: Multi-region backups, failover testing, high availability architecture.
• Infrastructure as Code: Terraform and Python for provisioning and lifecycle automation.
• Security & Compliance: Role-based access, SCIM provisioning, audit logging, governance enforcement.
• Cost & Performance: Cluster policy tuning, tagging, monitoring, and analytics.
• CI/CD: Automated deployment pipelines using GitHub Actions or similar tools.
• Cloud Integration: AWS services (S3, IAM, networking) and Databricks integrations.
• Observability: Monitoring, alerting, logging, and platform metrics dashboards