Databricks Administrator

Job Title: Databricks Administrator Location: Austin, TXWork Type: HybridEmployment Type: Contract (C2C)Duration: 4+ Months Interview Mode: In-person Only Open to LOCALS of Texas only About the Role: We are seeking a Databricks Administrator to manage, configure, and support the Databricks platform in a cloud environment (AWS). This role focuses on ensuring platform reliability, security, governance, and cost optimization while enabling scalable data engineering, analytics, and AI/ML workloads. This role is ideal for experienced Databricks administrators with strong AWS, Spark, and governance expertise, looking to support large-scale data and analytics platforms in a regulated environment. Key Responsibilities: Administer and manage Databricks workspaces in AWS cloud environments Configure and manage clusters, job scheduling, and workspace settings Implement and maintain RBAC, IAM, and SCIM-based access controls Enforce cluster policies and governance standards Monitor platform performance, health, and availability Integrate Databricks with cloud storage services (e.g., S3) Optimize Spark workloads and performance tuning Support data engineers, analysts, and data scientists Ensure data security, encryption, and compliance requirements Automate processes using Terraform, CI/CD pipelines, and scripting Support notebooks, Databricks SQL, and job orchestration workflowsRequired Skills: 8+ years of experience administering Databricks in AWS environments Strong expertise in: Cluster configuration and workspace management Job scheduling and orchestration 8+ years of hands-on experience with: IAM, SCIM, RBAC Apache Spark (performance tuning & troubleshooting) Experience integrating with AWS S3 and cloud storage Strong knowledge of: Platform monitoring and performance optimization Data security, encryption, and compliance Experience with DevOps/automation tools (Terraform, CI/CD, scripting) Familiarity with Databricks SQL, notebooks, and workflowsPreferred Skills: Experience in enterprise or government environments Hands-on with Unity Catalog (data governance) Knowledge of cost optimization strategies for Databricks Experience supporting AI/ML workloads (Databricks ML, MLflow) Understanding of data lake / lakehouse architectures Knowledge of Python, SQL, or Scala