Lead Databricks Platform Engineer for Azure ML & AI

Vizient; Irving (TX); On-site; USD 117,600 - 206,000; Full time

Job summary

Vizient seeks a senior leader to design, engineer, and evolve the enterprise Databricks platform as a strategic capability enabling analytics, data products, ML, and AI across the organization.

You will develop reusable platform services, automation frameworks, reference architectures, and self-service capabilities that accelerate delivery while aligning with governance and engineering standards.

Qualifications

• Advanced degree or equivalent in CS/engineering preferred.
• 7+ years of relevant experience.
• 3+ years designing and supporting Databricks platform solutions.
• Strong experience with Azure cloud services and lakehouse architectures.
• Experience with Terraform, CI/CD, and automation.

Responsibilities

• Lead design, implementation, and evolution of the enterprise Databricks platform.
• Develop reusable platform services and self-service capabilities.
• Build IaC, CI/CD pipelines, and automation frameworks.
• Create deployment templates and engineering accelerators.
• Optimize performance, security, governance, and cost efficiency.
• Enable ML/AI platform capabilities (MLflow, Model Registry, etc.).
• Collaborate with EA, Data Eng, Cloud Eng, Data Science, and stakeholders.
• Evaluate new Databricks features and lead PoCs and platform enhancements.
• Provide technical leadership and promote Platform-as-a-Product.

Skills

Databricks Platform

Azure cloud services

Platform engineering

Automation frameworks

Self-service capabilities

Mentoring

Leadership

Education

Advanced degree in Computer Science or related field

Relevant degree preferred

Tools

Terraform

Delta Lake

Unity Catalog

Apache Spark

MLflow

Model Registry

Feature Store

Job description

Vizient seeks a senior leader to design, engineer, and evolve the enterprise Databricks platform as a strategic capability enabling analytics, data products, ML, and AI across the organization.

You will develop reusable platform services, automation frameworks, reference architectures, and self-service capabilities that accelerate delivery while aligning with governance and engineering standards.