Staff Engineer, Databricks Platform

Modernizing Medicine, Inc.; United States; Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) match

PTO & parental leave

Hybrid/remote options

LinkedIn Learning access

Job summary

Modernizing Medicine, Inc. (ModMed) seeks a hands‑on Senior/Staff Data Platform Engineer to own and evolve our Databricks platform on AWS.

This role delivers shared infrastructure, guardrails, observability, and self‑service capabilities used by Data Engineering, Analytics, ML, and MLOps across regulated healthcare data. The position reports to the Director of Data Platform Engineering and begins as an individual contributor, with no initial direct reports.

Qualifications

• Ownership of Databricks on AWS in a multi‑team production environment.
• Experience with Unity Catalog, identity federation, service principals, and auditability.
• Proficiency in Terraform and IaC practices with CI/CD.
• Strong AWS knowledge across IAM, VPC, private connectivity, S3, KMS, and security.
• Experience with Spark and distributed computing.
• Python for automation, shell scripting, and REST API integration.
• Excellent communication and ability to influence across teams.

Responsibilities

• Own Databricks platform across development, test, and production environments; automate provisioning and governance.
• Manage Unity Catalog, metastore, credentials, lineage, and access controls; define compute patterns and policies.
• Lead IaC strategy with Terraform; build reusable modules and CI/CD workflows; ensure drift detection and security.
• Implement cloud guardrails, monitoring, budgeting, and cost optimization across workloads.
• Collaborate with Data Engineering, Analytics, ML, and DevOps teams to enable self-service platform capabilities.

Skills

Databricks on AWS

Unity Catalog

Terraform / IaC

AWS IAM & S3

Spark / distributed computing

Python automation

Communication skills

Tools

Terraform

Databricks

Job description

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 administration.
• Strong experience with Unity Catalog, identity federation, service principals, compute policies, secure data‑access patterns, lineage, and auditability.
• Deep production experience with Terraform and IaC practices, including modular infrastructure built with the Databricks and AWS providers, state management, source control, automated testing, and CI/CD.
• Strong AWS knowledge across IAM, VPC networking, private connectivity, S3, KMS, security groups, logging, and cross‑account access.
• Experience operating cloud data platforms containing regulated, confidential, or highly sensitive data.
• Experience with observability, incident response, change management, capacity planning, and cloud cost optimization.
• Experience leading a significant platform migration, workspace or metastore consolidation, runtime upgrade, or comparable modernization under production load.
• Working knowledge of Spark and distributed computing sufficient to diagnose platform and workload‑performance issues.
• Proficiency in Python for automation, plus practical shell scripting and REST API integration.
• Strong communication and influence skills, with demonstrated success establishing standards and self‑service guardrails across organizational boundaries.

Preferred qualifications

• Experience operating healthcare data platforms and implementing HIPAA‑aligned controls for PHI.
• Experience with MLflow, Models in Unity Catalog, model serving, GPU workloads, feature engineering platforms, or GenAI infrastructure.
• Experience with multi‑workspace, multi‑account, or multi‑region architectures and disaster‑recovery testing.
• Databricks and/or AWS professional certification. Certification is valuable but is not a substitute for production platform ownership.

Measures of success

Shared‑platform configurations are reproducible, peer‑reviewed, and version‑controlled through infrastructure as code. Privileged access and production changes follow least‑privilege and auditable approval practices. Within the first 90 days, establish measurable baselines for platform reliability, configuration drift, manual administrative effort, and unit cost; demonstrate sustained improvement against those baselines. Teams deploy approved workloads through documented, reusable, self‑service patterns. Databricks cost and commitment utilization are visible, attributable, forecastable, and optimized without compromising agreed reliability or performance.

Ownership boundaries

This role owns the Databricks platform and implementation of approved technical controls. Cloud Platform owns enterprise AWS foundations and guardrails. Cybersecurity and Data Governance define policy; data owners approve business access. Data Engineering, Analytics, and AI/ML teams own their code, data products, models, evaluations, and releases. The ML/AI/LLM Operations function owns model promotion, deployment automation, production monitoring, and rollback.

ModMed Benefits Highlight

• United States Comprehensive medical, dental, and vision benefits, including a company Health Savings Account contribution, 401(k): ModMed provides a matching contribution each payday of 50% of your contribution deferred on up to 6% of your compensation.
• After one year of employment with ModMed, 100% of any matching contribution you receive is yours to keep.
• Generous Paid Time Off and Paid Parental Leave programs, Company paid Life and Disability benefits, Flexible Spending Account, and Employee Assistance Programs.
• Company-sponsored Business Resource & Special Interest Groups that provide engaged and supportive communities within ModMed, Professional development opportunities, including tuition reimbursement programs and unlimited access to LinkedIn Learning, Global presence and in‑person collaboration opportunities; dog‑friendly HQ (US), Hybrid office‑based roles and remote availability for some roles, Weekly catered breakfast and lunch, treadmill workstations, Zen, and wellness rooms within our BRIC headquarters.