Staff Engineer, Databricks Platform

Join the Team Modernizing Medicine At  ModMed , we’re not just building software—we’re reimagining the healthcare experience. Founded in 2010 by a practicing physician and a successful tech entrepreneur, we took a radically different approach:  we hired doctors and taught them how to code.  This "for doctors, by doctors" philosophy has allowed us to create an AI-enabled, specialty-specific cloud platform that places patients at the center of care. A Culture of Excellence When you join ModMed, you’re joining an award-winning team recognized for innovation and employee satisfaction.   From our global headquarters in Boca Raton Florida, and extensive employee base in Hyderabad India, we are a team of 4,500+ passionate problem-solvers on a mission to increase medical practice success and improve patient outcomes: Consistently ranked as a Top Place to Work 2025 Globee Business Awards:  Gold Globee for “Technology Team of the Year” 2025 Black Book Awards:  Ranked #1 EHR in 11 Specialties Florida Venture Forum:  Venture-Backed Company of the Year We are growing fast, thinking big, and we are just getting started. Ready to modernize medicine with us? Job Description Summary: We are seeking a hands-on Senior/Staff Data Platform Engineer to own and evolve our established Databricks platform on AWS. The platform supports mission-critical data, analytics, and AI workloads built on regulated healthcare data across multiple teams and products. This is an individual-contributor technical leadership role reporting to the Director of Data Platform Engineering, with no direct reports initially. It is a platform-engineering role—not an application data-engineering, data-science, or MLOps role. You will engineer the shared foundation, guardrails, automation, observability, and self-service capabilities used by Data Engineering, Analytics, ML Engineering, AI Engineering, and MLOps. Key responsibilities Databricks platform ownership Own Databricks account- and workspace-level capabilities across development, test, and production environments. Automate workspace provisioning and configuration, including identity federation, SSO/SCIM integration, service principals, workspace assignments, entitlements, and administrative controls. Administer Unity Catalog, including metastores, workspace bindings, storage credentials, external locations, lineage, auditing, and implementation of the access model defined by Data Governance and data owners. Define approved patterns for serverless and classic compute, jobs, interactive compute, SQL warehouses, and specialized compute when required. Maintain compute policies, runtime and library standards, tagging, auto-termination, quotas, compatibility testing, and LTS/deprecation plans that balance security, performance, reliability, and cost. Infrastructure as Code (IaC), AWS integration, and security Own the IaC strategy and implementation for the Databricks platform, building and maintaining reusable Terraform modules with the Databricks and AWS providers. Manage supported account, workspace, Unity Catalog, compute, and AWS integration configurations through code, with environment isolation, automated plans and tests, approval controls, and configuration-drift detection and remediation. Build tested CI/CD workflows using  account, workspace, Unity Catalog, and shared-platform changes, including peer review, approvals, controlled promotion, and rollback. Provide reusable Declarative Automation Bundle templates—formerly Databricks Asset Bundles—and secure deployment patterns. Workload teams remain responsible for their code and releases. Consume enterprise AWS guardrails and partner with Cloud Platform to automate Databricks-specific networking, private connectivity, IAM, S3, KMS, DNS, secrets management, and connectivity with services such as Aurora and Kafka. Implement approved controls for PHI and other sensitive data, including encryption, network isolation and egress, privileged access, logging, approval workflows, access reviews, and break-glass procedures. Ensure privileged and account-level changes are reviewed and approved by designated Cloud Platform, Cybersecurity, or Data Governance partners based on the affected control. Support security reviews, audit evidence, risk remediation, and production change-management requirements. Reliability, observability, and FinOps Establish platform service levels, health indicators, alerts, dashboards, escalation paths, and runbooks using Databricks system tables, audit logs, CloudWatch Participate in a shared on-call and escalation rotation; lead diagnosis, root-cause analysis, and preventive action for complex Databricks and AWS integration incidents. Implement cost attribution, budgets, tagging, showback reporting, and optimization recommendations across teams and workloads. Track Databricks consumption against commercial commitments, forecast capacity, and provide technical analysis for planning and renewal decisions. Own Databricks recovery patterns and testing in partnership with Cloud Platform and workload owners, aligned with agreed recovery objectives. Data and AI platform enablement Build paved-road templates, standards, documentation, and support mechanisms that increase self-service and reduce one-off administrative requests. Partner with Data Engineering, Analytics, ML Engineering, AI Engineering, and MLOps to translate workload requirements into supported platform capabilities. Configure shared MLflow and Models in Unity Catalog capabilities and enable approved training, inference, and model-serving patterns as they are adopted. Troubleshoot platform issues without assuming ownership of pipeline logic, model development, evaluations, AI application behavior, or workload releases. Required qualifications Demonstrated ownership of Databricks on AWS in a multi-team production environment, including account- and workspace-level administratio