ML Administrator

Position Summary

The ML Administrator supports mission-critical objectives under the referenced work order by supporting Databricks platform administration and enterprise data architecture for DoD data-driven projects. This role manages knowledge graph metadata integration, data governance, and cataloging in Databricks Unity Catalog.

This future opportunity is contingent upon award.

Job Description

• The ML Administrator is responsible for managing Databricks platform administration including workspace management, cluster optimization, and Unity Catalog integration for secure data governance.


• The position requires developing ETL pipelines, Delta Lake architecture, and Data Lakehouse optimization for DoD analytics and mission-critical data workflows.


• Administrators will implement SysEngOps, DevSecOps, version control systems (Git), and CI/CD pipelines.


• The role includes managing knowledge graph metadata integration, data governance, and cataloging.

Required Qualifications and Experience

The contractor shall provide personnel who meet one of the following requirements:

• Master's degree or higher in Computer Science, Information Technology, Systems Engineering, Data Science, or a closely related field; or


• A minimum of eleven (11) years of professional experience in enterprise data architecture, Databricks administration, and cloud-based data platforms.

Candidates must have demonstrated experience in the following areas:

• Databricks platform administration including workspace configuration, Unity Catalog, and cluster performance tuning.


• Data pipeline development (ETL/ELT) and Delta Lake optimization.


• AI/ML workflow integration.


• SysEngOps, DevSecOps, version control systems (Git), and CI/CD pipelines for automated deployment and governance.


• Cloud security, role-based access control (RBAC), and compliance with DoD data policies across AWS, Azure, and GCP.

Required Skills and Competencies

• Expertise in Databricks platform administration, Unity Catalog, and cluster optimization.


• Working knowledge of ETL/ELT, Delta Lake, and AI/ML workflow integration.


• Proficiency in IAM, RBAC, Python, SQL/NoSQL, Apache Spark, and Terraform.


• Strong understanding of cloud-native data services for large-scale data processing and analytics.


• Ability to implement SysEngOps, DevSecOps, and CI/CD pipelines.

Education

• Master's degree or higher in a relevant field, or an equivalent combination of education and extensive experience.


• Platform-specific Databricks certifications (Preferred, Not Required)


• Cloud security certifications (Preferred, Not Required)

Clearance Requirement

• The ability to obtain and maintain the required clearance as specified by the program.