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Lead Software Engineer (Databricks Platform Engineer)

Vizient · Chicago, IL · $117,600–$206,000 a year · Full time

Posted Aug 17, 2026 · We last checked this listing on Oct 5, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Tell me about a reference architecture or engineering standard you created. How did you get teams to adopt it?

What they are checking: Driving platform adoption through developer experience and influence, not mandates.

Tell me about a platform outage or major incident you dealt with. What changed afterward?

What they are checking: Ownership under pressure and follow-through on reliability improvements.

How do you gather feedback from the teams using your platform, and how does it shape your roadmap?

What they are checking: Treating the platform as a product with users, which drives adoption and real developer experience gains.

What would you do

Databricks costs jumped 40 percent last month. How do you find out why and fix it?

What they are checking: Cost observability skills, from cluster policies to job tuning, and working with teams instead of blaming them.

A new Databricks feature looks promising but is still in preview. How do you decide whether to use it?

What they are checking: Evaluating emerging technology with discipline, weighing risk and support before betting the platform on it.

About the work

How would you design a Databricks platform so dozens of teams can self-serve without creating a governance mess?

What they are checking: Platform thinking around workspaces, Unity Catalog, templates and guardrails that make the right path the easy path.

Walk me through how you automate workspace, cluster and job provisioning. What tools have you used?

What they are checking: Infrastructure-as-code and CI/CD depth, since manual setup doesn't scale for an enterprise platform.

How do you decide what belongs in a shared platform service versus what each team should build themselves?

What they are checking: Judgment on reuse versus flexibility so the platform helps teams rather than slowing them.

How would you handle access control for sensitive healthcare data on the platform?

What they are checking: Practical knowledge of fine-grained permissions, row and column security and auditability for regulated data.

How do you support machine learning and AI workloads on the same platform as analytics and reporting?

What they are checking: Understanding of different compute, serving and governance needs across ML, AI and BI users.

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The full job description

As published by Vizient.

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 lead the design, engineering, and evolution of the enterprise Databricks platform as a strategic capability that enables analytics, data products, machine learning, and AI solutions across the organization. You will develop reusable platform services, automation frameworks, reference architectures, and self-service capabilities that accelerate delivery while aligning with enterprise architecture, governance, and engineering standards. You will collaborate with cross-functional teams to enhance developer experience, drive platform adoption, evaluate emerging technologies, and deliver scalable, secure, and cost-effective healthcare data and AI solutions. Responsibilities: • Lead the design, implementation, and continuous evolution of the enterprise Databricks platform and supporting architecture. • Develop reusable platform services, reference architectures, engineering standards, and implementation patterns for analytics, data products, streaming, and AI workloads. • Build Infrastructure-as-Code, CI/CD pipelines, and automation frameworks to improve platform scalability, reliability, and operational efficiency. • Create self-service capabilities, reusable templates, and engineering accelerators that simplify platform onboarding and deployment. • Optimize platform performance, scalability, security, governance, and cost efficiency across cloud environments. • Enable machine learning and AI platform capabilities by implementing patterns for MLflow, Model Registry, Feature Store, Vector Search, and other Databricks technologies. • Partner with Enterprise Architecture, Data Engineering, Product Management, Cloud Engineering, Data Science, and client stakeholders to deliver enterprise platform capabilities. • Evaluate emerging Databricks features and cloud technologies, lead proof-of-concepts, and recommend platform enhancements that support business objectives. • Provide technical leadership, mentoring, and engineering guidance while promoting Platform-as-a-Product principles and engineering best practices. • Drive continuous improvement through automation, innovation, and adoption of enterprise platform standards. Qualifications: • Relevant degree preferred. Advanced degree in Computer Science, Engineering, Information Systems, or a related field preferred. • 7 or more years of relevant experience required. • 3 or more years of hands-on experience designing, implementing, and supporting Databricks platform solutions required. • Strong experience with Azure cloud services, cloud-native architectures, and enterprise platform engineering required. • Experience with Terraform, Infrastructure-as-Code, and CI/CD pipelines, and infrastructure automation. • Strong knowledge of Delta Lake, Unity Catalog, Apache Spark, and lakehouse architectures. • Experience developing reusable platform services, automation frameworks, self-service capabilities, and engineering accelerators. • Experience supporting machine learning and AI platform capabilities, including MLflow, Model Registry, Feature Store, Vector Search, or MLOps practices preferred. • Databricks certification, experience with streaming and event-driven architectures, enterprise-scale data platforms, or healthcare industry experience 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 $117,600.00 to $206,000.00. This position is also incentive eligible. Vizient has a comprehensive benefits plan! Please view our benefits here: http://www.vizientinc.com/about-us/careers 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.

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