Databricks Administrator (hybrid)
About The Position
14546 – Databricks Administrator (hybrid) – Austin, TX Start Date : ASAP Type: Temporary Project Estimated Duration : 12 months with possible extensions Work Setting: Onsite with some hybrid work Only candidates able to relocate as required should apply to avoid removal from future consideration. Required: Experience administering Databricks workspaces in a cloud environment – AWS (8 years) Experience with Databricks cluster configuration, job scheduling, and workspace management. (8 years) Experience managing user access, roles, and permissions using IAM, SCIM, and role-based access control (RBAC). (8 years) Experience with Apache Spark concepts, including performance tuning and troubleshooting. (8 years) Experience integrating Databricks with cloud storage services (e.g., S3,) (8 years) Experience implementing and enforcing cluster policies and workspace governance standards. (8 years) Experience with Databricks SQL, notebooks, and job orchestration. (8 years) Experience monitoring platform health, performance, and availability. (8 years) Experience with data security, encryption, and compliance requirements. (8 years) Experience with DevOps or automation tools (Terraform, CI/CD pipelines, scripting). (8 years) Preferred: Experience administering Databricks in an enterprise or government environment. (4 years) Experience with Databricks Unity Catalog for data governance and access control. (4 years) Experience with cost management and optimization for Databricks workloads. (4 years) Experience supporting AI/ML workloads using Databricks ML and MLflow. (4 years) Experience with data lake and lakehouse architectures. (4 years) Experience with Python, SQL, or Scala for administration and troubleshooting. (4 years) Responsibilities: Administer, configure, and support the Databricks platform in AWS to enable scalable data engineering, analytics, and AI/ML workloads while ensuring platform reliability and availability. Manage workspace configuration, cluster policies, job scheduling, and overall workspace governance to align with enterprise standards. Configure and oversee user access, roles, and permissions using IAM, SCIM, and RBAC, ensuring appropriate security and compliance controls. Integrate Databricks with cloud storage services such as S3 and other cloud components required to support data and analytics initiatives. Monitor platform health, performance, and usage, proactively troubleshoot issues, and tune clusters and Spark workloads for optimal performance. Implement and enforce data security, encryption, and compliance requirements across Databricks environments, including Unity Catalog where applicable. Develop and maintain automation and DevOps practices using tools such as Terraform, CI/CD pipelines, and scripting to standardize deployments and operations.
Requirements
- Experience administering Databricks workspaces in a cloud environment – AWS (8 years)
- Experience with Databricks cluster configuration, job scheduling, and workspace management. (8 years)
- Experience managing user access, roles, and permissions using IAM, SCIM, and role-based access control (RBAC). (8 years)
- Experience with Apache Spark concepts, including performance tuning and troubleshooting. (8 years)
- Experience integrating Databricks with cloud storage services (e.g., S3,) (8 years)
- Experience implementing and enforcing cluster policies and workspace governance standards. (8 years)
- Experience with Databricks SQL, notebooks, and job orchestration. (8 years)
- Experience monitoring platform health, performance, and availability. (8 years)
- Experience with data security, encryption, and compliance requirements. (8 years)
- Experience with DevOps or automation tools (Terraform, CI/CD pipelines, scripting). (8 years)
Nice To Haves
- Experience administering Databricks in an enterprise or government environment. (4 years)
- Experience with Databricks Unity Catalog for data governance and access control. (4 years)
- Experience with cost management and optimization for Databricks workloads. (4 years)
- Experience supporting AI/ML workloads using Databricks ML and MLflow. (4 years)
- Experience with data lake and lakehouse architectures. (4 years)
- Experience with Python, SQL, or Scala for administration and troubleshooting. (4 years)
Responsibilities
- Administer, configure, and support the Databricks platform in AWS to enable scalable data engineering, analytics, and AI/ML workloads while ensuring platform reliability and availability.
- Manage workspace configuration, cluster policies, job scheduling, and overall workspace governance to align with enterprise standards.
- Configure and oversee user access, roles, and permissions using IAM, SCIM, and RBAC, ensuring appropriate security and compliance controls.
- Integrate Databricks with cloud storage services such as S3 and other cloud components required to support data and analytics initiatives.
- Monitor platform health, performance, and usage, proactively troubleshoot issues, and tune clusters and Spark workloads for optimal performance.
- Implement and enforce data security, encryption, and compliance requirements across Databricks environments, including Unity Catalog where applicable.
- Develop and maintain automation and DevOps practices using tools such as Terraform, CI/CD pipelines, and scripting to standardize deployments and operations.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
11-50 employees
