Senior Databricks Engineer

Experience administering Databricks workspaces in a cloud environment - AWS

Strong understanding of Databricks cluster configuration, job scheduling, and workspace management.

Experience managing user access, roles, and permissions using IAM, SCIM, and role-based access control (RBAC).

Proficiency with Apache Spark concepts, including performance tuning and troubleshooting.

Experience integrating Databricks with cloud storage services (e.g., S3,)

Experience implementing and enforcing cluster policies and workspace governance standards.

Familiarity with Databricks SQL, notebooks, and job orchestration.

Experience monitoring platform health, performance, and availability.

Understanding of data security, encryption, and compliance requirements.

Experience with DevOps or automation tools (Terraform, CI/CD pipelines, scripting).

Experience administering Databricks in an enterprise or government environment.

Experience with Databricks Unity Catalog for data governance and access control.

Knowledge of cost management and optimization for Databricks workloads.

Experience supporting AI/ML workloads using Databricks ML and MLflow.

Familiarity with data lake and lakehouse architectures.

Knowledge of Python, SQL, or Scala for administration and troubleshooting.