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We are seeking an experienced Senior Databricks Administrator to manage and optimize our Databricks platform in an AWS cloud environment. The ideal candidate will have strong expertise in Databricks workspace administration, Apache Spark, cloud integrations, and data platform governance. This role focuses on ensuring platform performance, security, scalability, and cost optimization for enterprise data and AI workloads.
Job Responsibility:
Administer and manage Databricks workspaces in AWS cloud environments
Configure and optimize Databricks clusters, job scheduling, and workspace settings
Manage user access, roles, and permissions using IAM, SCIM, and RBAC
Implement and enforce cluster policies and governance standards
Monitor platform health, performance, and availability
Optimize Apache Spark workloads for performance and scalability
Integrate Databricks with cloud storage services (e.g., Amazon S3)
Manage and support Databricks SQL, notebooks, and job orchestration
Ensure data security, encryption, and compliance requirements are met
Automate infrastructure and workflows using Terraform, scripting, and CI/CD pipelines
Support AI/ML workloads using Databricks ML and MLflow (as needed)
Requirements:
8+ years of experience in Databricks administration in AWS environments
Strong expertise in Databricks cluster configuration and workspace management
Hands-on experience with Apache Spark (performance tuning & troubleshooting)
Experience managing IAM, SCIM, and role-based access control (RBAC)
Experience integrating Databricks with cloud storage (S3 or similar)
Strong understanding of data security, encryption, and compliance
Experience with DevOps tools (Terraform, CI/CD pipelines, scripting)
Nice to have:
Experience in enterprise or government environments
Familiarity with Databricks Unity Catalog for governance
Experience with cost optimization strategies for Databricks workloads