Staff / Principal Forward-Deployed Architect, Data Modernization
Job Summary
The Staff / Principal Forward-Deployed Architect is the senior-most technologist in our Data Modernization Services function. They own the reference architecture that defines how we land an EHR-anchored, AI-ready data foundation on Databricks, Snowflake, and Microsoft Fabric, and they stay close enough to the work to ship code themselves when an engagement calls for it.
Key Responsibilities
Own the cross-platform reference architecture for the Modern Data Platform across Databricks, Snowflake, and Fabric — and evolve it as platforms and partners change
Lead the technical discovery with prospective health system partners — assess source environments (Epic Clarity/Caboodle, Cogito on Cloud, Bulk FHIR, flat-file SFTP) and design a defensible target state
Lead and develop a team of platform-specialist Senior Data Engineers and a Cloud/Platform Engineer; set the technical bar
Review and approve all engineering deliverables — IaC, ingestion patterns, data sharing topology, security controls
Partner with the Engagement Manager and Field CDO to scope SOWs, defend timelines, and surface technical risk before it becomes schedule risk
Coordinate technical handoffs to the QH Platform team via Delta Sharing / Reader Account so AI workflows can be deployed against the modernized foundation
Maintain the technical engagement playbook and a library of accelerators so each engagement starts further along than the last
Carry the technical narrative in pre-sales: present to CTOs, CDOs, and enterprise architects; convert technical credibility into signed work
Required Qualifications
Education: Bachelor's degree in Computer Science, Engineering, or a related field. Master's preferred
Experience: 10+ years in data engineering, data platform architecture, or solutions architecture roles, with demonstrated technical leadership of multi-person teams
Hands-on production experience across at least two of Databricks, Snowflake, and Microsoft Fabric — and the technical curiosity and pattern-recognition to credibly own the third
Three or more enterprise lakehouse / cloud data platform implementations delivered in regulated industries
Deep cloud fluency, with Azure as the most common engagement substrate: networking, identity, key management, IaC (Terraform or Bicep), and observability
Client-facing experience leading executive technical conversations — comfortable in a room with a health system CTO, CDO, or CISO
Healthcare data fluency: Epic Clarity / Caboodle, Cogito on Cloud, Bulk FHIR, HL7, claims data, and the realities of on-prem-to-cloud CDC
Direct experience with modern data sharing patterns: Delta Sharing, Snowflake Reader Accounts, Fabric External Sharing, Iceberg shortcuts
HIPAA / HITRUST-regulated environments; opinions on PHI segmentation, BAA scope, and audit posture
Background in a Databricks / Snowflake / Microsoft Fabric professional services or field engineering org, a healthcare-focused consultancy, or a large IDN data platform team
Track record of architecting under a time-boxed engagement (e.g., 8–10 week greenfield delivery) rather than open-ended programs
Desirable Skills
Multi-Platform Judgment: You don't get religious about Databricks vs Snowflake vs Fabric. You can articulate when each is the right call for a given customer's data gravity, existing investments, and roadmap — and design accordingly
Architect Who Still Builds: You lead by example. You review IaC and PySpark, you pair on the hardest design problems, and you'll personally drive the build on the gnarliest part of an engagement instead of throwing it over the wall
Pragmatism: You know the difference between the architecturally ideal target and what a 10-week engagement can realistically land — and you optimize for delivered value without quietly accumulating technical debt
Pre-Sales Presence: You can walk into a discovery session cold, ask the right five questions, and leave with a credible architectural sketch. You convert technical depth into customer confidence
Strong Opinions, Loosely Held: You bring a point of view to every architecture review, defend it well, and update it cleanly when the customer environment or new information argues against you
Documentation Discipline: You treat the playbook as a product. Every engagement leaves behind patterns, accelerators, and decisions the next engagement inherits