Job VC

Our client is a performance rights organization in the United States. It collects blanket license fees from businesses that use music, entitling those businesses to play or sync any songs from the client’s repertoire of over 22.4 million musical works. On a regular basis, the client distributes the money to songwriters, composers, and music publishers as royalties to those members whose works have been performed.
Requirements:
Databricks Expertise:
Minimum of 3+ years of proven, previous Databricks administration experience in a complex, multi-tenant enterprise environment.
Advanced Terraform:
Strong Terraform skills. You must have hands-on experience building and maintaining reusable modules specifically utilizing the Databricks Terraform Provider.
Strong understanding of cloud-native IaC
(Infrastructure as Code) like Terraform for automating instance provisioning
Cloud IAM Mastery
: Deep, practical knowledge of Cloud Identity and Access Management (IAM), including writing secure IAM policies, managing roles, cross-account access, and secrets management.
Robust
cloud networking
experience
Scripting
: Proficiency in Bash
Job responsibilities:
Environment Ownership:
Own the technical implementation of all Databricks environment configuration changes across multi-workspace environments.
Platform Lifecycle:
Manage Databricks runtimes, cluster policies, and coordinate seamless platform upgrades.
Infrastructure as Code (IaC)
: Utilize strong Terraform skills to programmatically provision, update, and manage all Databricks resources (workspaces, clusters, tokens, policies) and cloud infrastructure, eliminating manual configurations.
Cloud Security & Identity (IAM):
Architect and enforce secure access models. Manage Cloud Identity and Access Management (IAM) integrations for users, groups, and service principals.
Secure Cloud Networking:
Design, implement, and maintain secure cloud networking architectures for Databricks.
Cost Optimization:
Actively review current environment setups—including cluster configurations, instance types, and data storage parameters—to identify and execute cost-optimization opportunities.
Efficiency Strategies:
Provide expert input on automation, auto-scaling, and monitoring strategies to drastically reduce ongoing compute and storage costs.