Job description

When you’re the best, we’re the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves . We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future. Summary: In this role, you will design, build, and enhance the enterprise Databricks platform to support analytics, data products, machine learning, and AI initiatives across the organization. You will collaborate with Enterprise Architecture, Data Engineering, Product Management, Cloud Engineering, and Data Science teams to develop reusable platform services, automation frameworks, engineering standards, and self-service capabilities that improve platform adoption, developer experience, and engineering productivity while advancing the organization s enterprise data and AI platform. Responsibilities: Develop and enhance enterprise Databricks platform capabilities that support analytics, data products, machine learning, and AI workloads. Implement platform architectures, engineering standards, and reusable design patterns aligned with enterprise technology strategies. Build and maintain Infrastructure-as-Code solutions, CI/CD pipelines, and platform automation to improve consistency and operational efficiency. Create reusable templates, accelerators, and deployment patterns that enable self-service platform adoption and solution delivery. Optimize platform scalability, performance, reliability, and cost efficiency across cloud environments. Collaborate with Enterprise Architecture, Cloud Engineering, Data Engineering, Product Management, and Data Science teams to operationalize platform capabilities. Support platform services including MLflow, Model Registry, Feature Store, Vector Search, and related Databricks capabilities. Evaluate emerging Databricks features and cloud technologies through technical assessments and proof-of-concepts. Recommend platform enhancements, automation opportunities, and engineering best practices that improve developer experience and platform maturity. Contribute to the evolution of enterprise platform standards, reference architectures, and strategic roadmap initiatives. Qualifications: Relevant degree preferred. 5 or more years of relevant experience required. 2 or more years of hands-on experience with the Databricks platform required. Experience with Azure cloud services and cloud-native architectures preferred. Experience developing and maintaining Infrastructure-as-Code solutions using Terraform and CI/CD pipelines. Strong knowledge of Delta Lake, Unity Catalog, Apache Spark, and lakehouse architecture concepts. Experience developing automation solutions and reusable engineering components. Experience with MLflow, MLOps, AI platform technologies, streaming, or event-driven architectures preferred. Strong analytical, problem-solving, collaboration, and communication skills. Experience supporting enterprise-scale data platforms and healthcare or other regulated environments preferred. Estimated Hiring Range: At Vizient, we consider skills, experience, and organizational needs in our compensation approach. Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $102,400.00 to $179,000.00. This position is also incentive eligible. Vizient has a comprehensive benefits plan! Please view our benefits here: vizientinc.com Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.

Requirements

Must-haves

Develop and enhance enterprise Databricks platform capabilities that support analytics, data products, machine learning, and AI workloads.
Implement platform architectures, engineering standards, and reusable design patterns aligned with enterprise technology strategies.
Build and maintain Infrastructure-as-Code solutions, CI/CD pipelines, and platform automation to improve consistency and operational efficiency.
Create reusable templates, accelerators, and deployment patterns that enable self-service platform adoption and solution delivery.
Optimize platform scalability, performance, reliability, and cost efficiency across cloud environments.
Collaborate with Enterprise Architecture, Cloud Engineering, Data Engineering, Product Management, and Data Science teams to operationalize platform capabilities.
Support platform services including MLflow, Model Registry, Feature Store, Vector Search, and related Databricks capabilities.
Evaluate emerging Databricks features and cloud technologies through technical assessments and proof-of-concepts.
Recommend platform enhancements, automation opportunities, and engineering best practices that improve developer experience and platform maturity.
Contribute to the evolution of enterprise platform standards, reference architectures, and strategic roadmap initiatives.
5 or more years of relevant experience required.
2 or more years of hands-on experience with the Databricks platform required.
Experience developing and maintaining Infrastructure-as-Code solutions using Terraform and CI/CD pipelines.
Strong knowledge of Delta Lake, Unity Catalog, Apache Spark, and lakehouse architecture concepts.
Experience developing automation solutions and reusable engineering components.
Strong analytical, problem-solving, collaboration, and communication skills.
Vizient has a comprehensive benefits plan! Please view our benefits here:
Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities

Nice-to-haves

Relevant degree preferred.
Experience with Azure cloud services and cloud-native architectures preferred.
Experience with MLflow, MLOps, AI platform technologies, streaming, or event-driven architectures preferred.
Experience supporting enterprise-scale data platforms and healthcare or other regulated environments preferred.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaici/cdazure

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Professional Development