Databricks Platform Engineer: Build AI-Ready Analytics

Vizient; Edina (MN); On-site; USD 102,000 - 179,000; Full time

Benefits offered by this job

Incentive eligible

Comprehensive benefits

Job summary

Vizient is seeking an experienced professional to design, build, and enhance the enterprise Databricks platform to support analytics, data products, ML, and AI initiatives. You will collaborate with Enterprise Architecture, Data Engineering, Product Management, Cloud Engineering, and Data Science teams to deliver reusable platform services and automation that improve adoption and productivity.

The role focuses on scalable, secure, and cost-efficient platform capabilities, including MLflow and

Qualifications

• 5+ years of relevant experience in data platforms or analytics
• 2+ years hands-on experience with the Databricks platform
• Terraform and CI/CD experience for IaC
• Strong knowledge of Delta Lake and Spark lakehouse concepts

Responsibilities

• Develop and enhance enterprise Databricks platform capabilities for analytics and AI workloads
• Implement platform architectures, engineering standards, and reusable design patterns
• Build and maintain Infrastructure-as-Code solutions, CI/CD pipelines, and platform automation
• Create reusable templates and deployment patterns to enable self-service platform adoption
• Optimize platform scalability, performance, reliability, and cost efficiency across cloud environments
• Collaborate with EA, Cloud Eng., Data Eng., PM, and Data Science teams
• Support platform services including MLflow, Model Registry, and Feature Store

Skills

Databricks platform

5+ years experience

Azure cloud services

Automation solutions

Education

Bachelor's degree preferred

Tools

Terraform

Delta Lake

Unity Catalog

Apache Spark

MLflow

MLOps

Job description

Vizient is seeking an experienced professional to design, build, and enhance the enterprise Databricks platform to support analytics, data products, ML, and AI initiatives. You will collaborate with Enterprise Architecture, Data Engineering, Product Management, Cloud Engineering, and Data Science teams to deliver reusable platform services and automation that improve adoption and productivity.

The role focuses on scalable, secure, and cost-efficient platform capabilities, including MLflow and