Eligability: This opportunity is open to both C2C and W2 engagement model
We're looking for an experienced Databricks Platform Engineer to own and optimise an enterprise Databricks environment hosted on AWS.
This is a platform engineering role focused on infrastructure, security, governance, automation and operational excellence, not data engineering or analytics development. You'll work closely with Cloud, DevOps, Security and Data teams to ensure the platform is secure, scalable and cost-effective.
What You'll Be Doing
- Administer and support Databricks workspaces across Development, Test, UAT and Production.
- Manage platform upgrades, Databricks Runtime versions and environment standards.
- Configure and maintain cluster policies, instance pools and compute governance.
- Implement and manage Unity Catalog, RBAC and enterprise security controls.
- Integrate Databricks with AWS IAM, SSO, Secret Scopes and Service Principals.
- Build and maintain Infrastructure as Code using Terraform.
- Support Git integration and CI/CD pipelines for platform deployments.
- Monitor platform health, troubleshoot production issues and drive continuous improvements.
- Optimise platform performance and cloud costs through effective resource management.
- Maintain audit logging, governance standards and operational documentation.
What We're Looking For
- 5+ years' experience in IT, with 3+ years administering Databricks in production AWS environments.
- Strong hands-on experience with Databricks platform administration.
- Experience managing Unity Catalog, cluster policies and workspace governance.
- Solid AWS knowledge, including IAM, VPC, S3, EC2, KMS and CloudWatch.
- Experience with Terraform and Infrastructure as Code.
- Knowledge of Git, CI/CD and DevOps best practices.
- Experience supporting enterprise production platforms, monitoring and incident management.
- Strong understanding of security, governance and cloud cost optimisation.
Nice to Have
- Delta Lake and Lakehouse Architecture.
- AWS Organizations or Control Tower.
- PrivateLink or VPC Endpoints.
- Datadog, Splunk or other monitoring platforms.
- Apache Spark internals or AI/ML workloads.
- AWS, Databricks or Terraform certifications.
