{"id":3898552,"url":"https://alion.io/job/modmed-staff-engineer-databricks-platform","title":"Staff Engineer, Databricks Platform","company":{"id":1865761,"name":"ModMed","domain":"modmed.com","url":"https://alion.io/company/modmed","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":81,"open_postings":9,"ghost_share":0,"stale_share":0.778,"repost_share":0,"time_to_fill_p50_days":35,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Boca Raton, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Aurora","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"DNS","optional":false},{"name":"FinOps","optional":false},{"name":"IAM","optional":false},{"name":"MLFlow","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"HIPAA","optional":true},{"name":"Least Privilege","optional":true},{"name":"LLM","optional":true}],"status":"live","first_seen_at":"2026-11-06T23:52:14Z","employer_posted_date":"2026-11-06","last_verified_at":"2026-11-07T05:08:46Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Join the Team Modernizing Medicine\nAt 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.\nA Culture of Excellence\nWhen 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:\nConsistently ranked as a Top Place to Work\n\n2025 Globee Business Awards: Gold Globee for “Technology Team of the Year”\n\n2025 Black Book Awards: Ranked #1 EHR in 11 Specialties\n\nFlorida Venture Forum: Venture-Backed Company of the Year\n\nWe are growing fast, thinking big, and we are just getting started.\nReady to modernize medicine with us?\nJob Description Summary:\nWe 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.\nThis 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.\nKey responsibilities\nDatabricks platform ownership\nOwn Databricks account- and workspace-level capabilities across development, test, and production environments.\nAutomate workspace provisioning and configuration, including identity federation, SSO/SCIM integration, service principals, workspace assignments, entitlements, and administrative controls.\nAdminister 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.\nDefine approved patterns for serverless and classic compute, jobs, interactive compute, SQL warehouses, and specialized compute when required.\nMaintain compute policies, runtime and library standards, tagging, auto-termination, quotas, compatibility testing, and LTS/deprecation plans that balance security, performance, reliability, and cost.\nInfrastructure as Code (IaC), AWS integration, and security\nOwn the IaC strategy and implementation for the Databricks platform, building and maintaining reusable Terraform modules with the Databricks and AWS providers.\nManage 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.\nBuild tested CI/CD workflows using account, workspace, Unity Catalog, and shared-platform changes, including peer review, approvals, controlled promotion, and rollback.\nProvide reusable Declarative Automation Bundle templates-formerly Databricks Asset Bundles-and secure deployment patterns. Workload teams remain responsible for their code and releases.\nConsume 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.\nImplement 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.\nEnsure privileged and account-level changes are reviewed and approved by designated Cloud Platform, Cybersecurity, or Data Governance partners based on the affected control.\nSupport security reviews, audit evidence, risk remediation, and production change-management requirements.\nReliability, observability, and FinOps\nEstablish platform service levels, health indicators, alerts, dashboards, escalation paths, and runbooks using Databricks system tables, audit logs, CloudWatch\nParticipate in a shared on-call and escalation rotation; lead diagnosis, root-cause analysis, and preventive action for complex Databricks and AWS integration incidents.\nImplement cost attribution, budgets, tagging, showback reporting, and optimization recommendations across teams and workloads.\nTrack Databricks consumption against commercial commitments, forecast capacity, and provide technical analysis for planning and renewal decisions.\nOwn Databricks recovery patterns and testing in partnership with Cloud Platform and workload owners, aligned with agreed recovery objectives.\nData and AI platform enablement\nBuild paved-road templates, standards, documentation, and support mechanisms that increase self-service and reduce one-off administrative requests.\nPartner with Data Engineering, Analytics, ML Engineering, AI Engineering, and MLOps to translate workload requirements into supported platform capabilities.\nConfigure shared MLflow and Models in Unity Catalog capabilities and enable approved training, inference, and model-serving patterns as they are adopted.\nTroubleshoot platform issues without assuming ownership of pipeline logic, model development, evaluations, AI application behavior, or workload releases.\nRequired qualifications\nDemonstrated ownership of Databricks on AWS in a multi-team production environment, including account- and workspace-level administration.\nStrong experience with Unity Catalog, identity federation, service principals, compute policies, secure data-access patterns, lineage, and auditability.\nDeep 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.\nStrong AWS knowledge across IAM, VPC networking, private connectivity, S3, KMS, security groups, logging, and cross-account access.\nExperience operating cloud data platforms containing regulated, confidential, or highly sensitive data.\nExperience with observability, incident response, change management, capacity planning, and cloud cost optimization.\nExperience leading a significant platform migration, workspace or metastore consolidation, runtime upgrade, or comparable modernization under production load.\nWorking knowledge of Spark and distributed computing sufficient to diagnose platform and workload-performance issues.\nProficiency in Python for automation, plus practical shell scripting and REST API integration.\nStrong communication and influence skills, with demonstrated success establishing standards and self-service guardrails across organizational boundaries.\nPreferred qualifications\nExperience operating healthcare data platforms and implementing HIPAA-aligned controls for PHI.\nExperience with MLflow, Models in Unity Catalog, model serving, GPU workloads, feature engineering platforms, or GenAI infrastructure.\nExperience with multi-workspace, multi-account, or multi-region architectures and disaster-recovery testing.\nDatabricks and/or AWS professional certification. Certification is valuable but is not a substitute for production platform ownership.\nMeasures of success\nShared-platform configurations are reproducible, peer-reviewed, and version-controlled through infrastructure as code.\nPrivileged access and production changes follow least-privilege and auditable approval practices.\nWithin the first 90 days, establish measurable baselines for platform reliability, configuration drift, manual administrative effort, and unit cost; demonstrate sustained improvement against those baselines.\nTeams deploy approved workloads through documented, reusable, self-service patterns.\nDatabricks cost and commitment utilization are visible, attributable, forecastable, and optimized without compromising agreed reliability or performance.\nOwnership boundaries\nThis 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.\nModMed Benefits Highlight: At ModMed, we believe it’s important to offer a competitive benefits package designed to meet the diverse needs of our growing workforce. Eligible Modernizers can enroll in a wide range of benefits:\nUnited States\nComprehensive medical, dental, and vision benefits, including a company Health Savings Account contribution,\n401(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.\nGenerous Paid Time Off and Paid Parental Leave programs,\nCompany paid Life and Disability benefits, Flexible Spending Account, and Employee Assistance Programs,\nCompany-sponsored Business Resource & Special Interest Groups that provide engaged and supportive communities within ModMed,\nProfessional development opportunities, including tuition reimbursement programs and unlimited access to LinkedIn Learning,\nGlobal presence and in-person collaboration opportunities; dog-friendly HQ (US), Hybrid office-based roles and remote availability for some roles,\nWeekly catered breakfast and lunch, treadmill workstations, Zen, and wellness rooms within our BRIC headquarters.\nPHISHING SCAM WARNING: ModMed is among several companies recently made aware of a phishing scam involving imposters posing as hiring managers recruiting via email, text and social media. The imposters are creating misleading email accounts, conducting remote \"interviews,\" and making fake job offers in order to collect personal and financial information from unsuspecting individuals. Please be aware that no job offers will be made from ModMed without a formal interview process, and valid communications from our hiring team will come from our employees with a ModMed email address ().Please check senders’ email addresses carefully. Additionally, ModMed will not ask you to purchase equipment or supplies as part of your onboarding process. 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