paycor
Databricks Platform Engineer
PCI Professional Services LLC
Remote, USA
Contract
Senior Level
Remote
Discovered 1 weeks ago
Free
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- Build, maintain, and optimize the enterprise data lakehouse infrastructure.
- Platform provisioning, monitoring, cost optimization, and providing technical support for Databricks workloads.
- Build and maintain Databricks workspace infrastructure across development, staging, and production environments
- Design, implement, and maintain Databricks platforms in cloud environments (Azure, AWS, or GCP), ensuring scalability, reliability, and cost-efficiency. Manage and optimize Databricks clusters, including autoscaling, resource allocation, monitoring, and troubleshooting.
- Oversee the deployment and configuration of Databricks workspaces, including user management, access controls, and workspace policies.
- Collaborate with infrastructure and DevOps teams to implement CI/CD pipelines for deploying Databricks workflows and notebooks. Monitor and manage performance, logging, and system health of the Databricks platform. Implement robust data security and governance measures in compliance with organizational policies and standards.
- Work with cross-functional teams to troubleshoot and resolve platform-related issues.
- Automate repetitive tasks, such as provisioning, upgrades, and scaling, using Infrastructure-as-Code (IaC) tools like Terraform or CloudFormation.
- Enable data engineers and data scientists by providing support for integrating Databricks with various data sources and tools.
- Stay up-to-date with the latest Databricks features, updates, and best practices to ensure the platform meets evolving business needs.
- Bachelor's degree in related discipline
- 5+ years of experience in platform engineering, cloud infrastructure, or IT operations, with 2+ years of hands-on experience managing Databricks environments.
- Public Trust (or higher) clearance eligibility
- Strong knowledge of Databricks administration, including cluster setup, workspace management, and job orchestration.
- Proficiency in Apache Spark for distributed data processing.
- Hands-on experience with cloud platforms (Azure Government, AWS GovCloud, or GCP Public Sector).
- Proficiency in scripting and automation with Python, Bash, or PowerShell.
- Experience with Infrastructure-as-Code (IaC) tools like Terraform, CloudFormation, or ARM templates.
- Solid understanding of cloud networking concepts, such as VPCs, subnets, security groups, and private endpoints.
- Familiarity with federal compliance frameworks, including FedRAMP, FISMA, NIST 800-53, and CMMC.
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