Databricks Platform Engineer

About the role

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you. The Databricks Platform Engineer is responsible for building, maintaining, and optimizing the cloud-based data platform that supports analytics, reporting, and data product development across the organization. This role focuses on the operational side of data engineering, including platform administration, infrastructure automation, data ingestion capabilities, governance implementation, and platform reliability. Working independently with limited direction, this individual partners with data engineers, architects, analysts, and business stakeholders to ensure the enterprise data platform remains scalable, secure, and efficient. The ideal candidate combines hands-on experience with Databricks administration, cloud infrastructure, and data engineering best practices to enable high-quality data solutions. Priority will be given to candidates who reside in the Columbus, OH metropolitan area. We are unable to provide sponsorship for this role presently or in the future.

Responsibilities

• Administer and maintain Databricks environments supporting enterprise analytics and data engineering workloads.
• Manage platform configurations, cluster performance, capacity planning, and operational stability.
• Monitor platform health and troubleshoot performance, reliability, and operational issues.
• Support lifecycle management of platform resources across development, testing, and production environments.
• Develop and maintain Infrastructure as Code solutions using Terraform.
• Support cloud-based data infrastructure within Azure environments.
• Implement automation to improve platform consistency, reliability, and operational efficiency.
• Partner with infrastructure and security teams to ensure adherence to enterprise standards.
• Build and support data ingestion frameworks and pipelines that enable reliable movement of data across platforms.
• Collaborate with Data Engineers to improve platform capabilities and optimize data processing workloads.
• Support structured and unstructured data workloads within cloud data environments.
• Assist in identifying and resolving data performance bottlenecks.
• Support data governance initiatives using Databricks Unity Catalog.
• Implement and maintain data access controls, permissions, and governance standards.
• Ensure compliance with organizational security and data management requirements.
• Contribute to metadata, lineage, and data quality practices.
• Evaluate new tools, technologies, and platform capabilities.
• Recommend improvements that enhance scalability, reliability, and developer productivity.
• Document platform standards, operational procedures, and support processes.