Remote Databricks Platform Engineer for Enterprise AI

Blu Omega LLC; Atlanta (GA); Hybrid; USD 140,000 - 155,000; Full time

Benefits offered by this job

Medical, Dental, and Vision coverage

401(k) with company match

Life and AD&D insurance

Short-term disability

EAP with mental health resources

Telehealth and virtual care

Pet insurance

Paid Time Off

Paid federal holidays

Wellness programs

Job summary

Blu Omega LLC is seeking a Sr Databricks Platform Engineer for a hybrid/Remote role that supports federal data analytics initiatives. You will manage Databricks environments, build automated provisioning, and enforce governance with Unity Catalog, while optimizing performance and cost across AWS and GCP.

The position requires strong data engineering and AI/ML workflow experience. Responsibilities include designing scalable data pipelines, supporting Genie-based tooling, and providing leadership

Qualifications

• 5+ years of experience managing Databricks environments, including governance, security, and configuration.
• Experience optimizing performance, scalability, and cost efficiency of Databricks environments.
• Proficiency with managing data pipelines and workflows using Lakeflow Designer, Pipelines, and Jobs.
• Experience with Genie Code and Genie Agents.
• Hands-on experience with Databricks SQL, queries, and dashboards.
• Strong understanding of Unity Catalog, governance, and enterprise data-security practices.
• Experience working with large datasets and distributed systems across AWS and GCP.
• Knowledge of CI/CD, automation, containerization, and cloud engineering principles.
• Strong troubleshooting and analytical skills.
• Excellent communication and documentation skills.
• Ability to work onsite in Atlanta, Georgia.
• Ability to obtain and maintain a Public Trust or Suitability/Fitness determination.
• Bachelor’s degree in computer science, information technology, engineering, data science, or a related field.

Responsibilities

• Administer and maintain Databricks accounts and workspaces, including configuration, governance, security, and access controls.
• Design and implement automated solutions for platform provisioning, configuration, and ongoing management.
• Establish and maintain enterprise governance and data-security controls using Unity Catalog and security best practices.
• Develop and support data pipelines and workflows utilizing Lakeflow Designer, Lakeflow Pipelines, and Lakeflow Jobs.
• Configure and support Genie Code and Genie Agents to enhance data engineering and analytics workflows.
• Architect and integrate autonomous AI agents and Model Context Protocol (MCP) servers for enterprise AI applications.
• Support Databricks SQL capabilities, including queries and dashboards for analytics and reporting.
• Monitor and optimize platform performance, scalability, reliability, and cost efficiency across AWS and GCP cloud environments.
• Collaborate with data engineering, science, and business teams to develop scalable platform solutions.
• Provide technical leadership and guidance on Databricks architecture, security, and best practices.
• Evaluate emerging Databricks capabilities for adoption and integration.
• Develop technical documentation and operational procedures to promote knowledge sharing.

Skills

Databricks governance

Databricks security

Databricks optimization

Lakeflow workflows

Genie Code/Genie Agents

Databricks SQL dashboards

CI/CD & automation

Cloud engineering principles

AWS & GCP experience

Troubleshooting & analytics

Communication & documentation

Security clearance eligibility

Education

Bachelor's degree in CS/IT/Engineering/Data Science

Tools

Docker

Kubernetes

Lakeflow Designer

Lakeflow Pipelines

Lakeflow Jobs

Genie Code

Genie Agents

Databricks SQL

Unity Catalog

Job description

Blu Omega LLC is seeking a Sr Databricks Platform Engineer for a hybrid/Remote role that supports federal data analytics initiatives. You will manage Databricks environments, build automated provisioning, and enforce governance with Unity Catalog, while optimizing performance and cost across AWS and GCP.

The position requires strong data engineering and AI/ML workflow experience. Responsibilities include designing scalable data pipelines, supporting Genie-based tooling, and providing leadership