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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Databricks Administrator / Platform Engineer - **Company:** General Dynamics Information Technology - **Location:** United States (Remote available) - **Experience:** Experienced - **Salary:** $113,900.0 - $154,100.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Audit Trail, Microsoft Azure, Information Engineering, Python (Programming Language), Key Management, Metadata, Meta-Data Management, Metadata Standards, Performance Tuning, Role-Based Access Control, Azure Machine Learning, SQL Databases, User Provisioning Software, Apache Spark, Multi-Cloud, Pyspark, Infrastructure Automation Frameworks, Machine Learning Operations, Terraform, Databricks - **Published:** July 12, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=1c2ecefda460f505 ## About the Role This role is ideal for someone who combines strong hands-on Databricks administration experience with practical data engineering skills and the ability to influence platform standards. The successful candidate will not only keep the platform running, but also help improve how the platform is structured, governed, and used across teams., * 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. #GDITFedHealthJobs Work Requirements Years of Experience 5 + years of related experience * may vary based on technical training, certification(s), or degree Certification Databricks Certified Data Engineer Professional | Databricks - Databricks ## Description GDIT 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, storage integrations, compute governance, and secure platform operations. The position also serves as a technical advisor to governance, FinOps, and engineering stakeholders by shaping platform design decisions, operational policies, and best practices for scalable and well-governed data product development., * 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. ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Crafting Custom Frameworks with Rust: A Deep Dive into Procedural Macros](https://www.wearedevelopers.com/videos/849-crafting-custom-frameworks-with-rust-a-deep-dive-into-procedural-macros) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)