Databricks Administrator / Platform Engineer

General Dynamics Information Technology is seeking an experienced Databricks Administrator / Platform Engineer to lead administration, governance, and operational management of an enterprise Databricks environment. This role is responsible for core platform administration across workspaces, Unity Catalog, access controls, and secure platform operations while advising governance and engineering stakeholders on best practices for data product development.

Responsibilities:

• Administer and maintain Databricks workspaces, catalogs, schemas, storage integrations, permissions, and platform configurations
• Manage Unity Catalog structures, including catalogs, schemas, external locations, storage credentials, grants, metadata standards, and governance controls
• Support user provisioning, group membership, RBAC/ABAC models, service principals, secrets management, and secure access patterns across the platform
• Define and enforce operational standards for cluster policies, compute governance, runtime management, workspace security, and scalable platform usage
• Troubleshoot platform issues related to permissions, connectivity, compute usage, storage access, workspace administration, and job execution
• Contribute data engineering expertise to platform best practices, including ingestion, transformation, orchestration, data quality, and performance optimization patterns
• Advise governance teams on standards for curated data products, metadata, tagging, lineage, and data quality expectations
• Partner with security, cloud, and engineering teams to improve monitoring, auditability, policy enforcement, and administrative guardrails
• Support cost optimization efforts by recommending best practices for workload management, cluster sizing, autoscaling, scheduling, and efficient resource usage
• Participate in platform design discussions, architecture reviews, and operational planning to improve scalability, maintainability, and governance maturity
• Create and maintain documentation, standards, runbooks, and repeatable operating procedures for platform administration and governed delivery
• As needed, provide platform-level guidance for adjacent analytics and AI capabilities in alignment with governance and operational standards

Requirements:

• Technical training/certification(s) and 5+ years of Databricks administration, platform engineering, or data engineering operations
• 3+ years of hands-on experience administering Databricks in an enterprise environment
• Strong experience with Unity Catalog, workspace administration, permissions management, user/group access controls, and storage integrations
• Practical data engineering experience using SQL, Python, PySpark, or Spark in support of pipeline troubleshooting, platform standards, and engineering collaboration
• Strong understanding of Databricks security best practices, including RBAC, ABAC, least privilege, cluster policies, secrets management, and secure workspace configuration
• Experience supporting governance initiatives such as metadata management, tagging, lineage, access policies, or data quality standards
• Familiarity with AWS, Azure, or multi-cloud Databricks environments
• Experience balancing hands-on administrative responsibilities with strategic advisory work on platform design, policies, and best practices
• Must be able to obtain and maintain a Public Trust
• Databricks certifications strongly preferred
• Experience advising on or implementing governance standards for curated or gold data products
• Strong written and verbal communication skills, including documentation and cross-functional stakeholder engagement
• Familiarity with FinOps practices, platform cost monitoring, and workload optimization in Databricks
• Experience with Databricks administrative capabilities such as audit logs, cluster policies, account console administration, workspace automation, and policy-driven governance
• Experience with Terraform, Databricks CLI, CI/CD pipelines, or infrastructure automation
• Exposure to Databricks analytics, reporting, model serving, or AI/ML platform capabilities
• Familiarity with enterprise metadata, lineage, and tagging strategies in regulated environments
• Databricks certification such as Data Engineer Associate/Professional or equivalent Databricks administration accreditation