Qualified Health is a Palo Alto–based enterprise AI platform and strategic partner that helps health systems deploy, govern, and scale AI across clinical and operational workflows.
Transform healthcare with us. At Qualified Health, we're redefining what's possible with Generative AI in healthcare. Our infrastructure provides the guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring — working alongside leading health systems to drive real change. This is more than just a job. It's an opportunity to build the future of AI in healthcare, solve complex challenges, and make a lasting impact on patient care. If you're ambitious, innovative, and ready to move fast, we'd love to have you on board. Join us in shaping the future of healthcare. JOB SUMMARY The Staff / Principal Forward-Deployed Architect is the senior-most technologist in our Data Modernization Services function — and the single named architect across every engagement we run. You own the reference architecture that defines how we land an EHR-anchored, AI-ready data foundation on Databricks, Snowflake, and Microsoft Fabric, and you stay close enough to the work to ship code yourself when an engagement calls for it. The work is unusually high-leverage. Every health system we modernize — from legacy reporting databases and SFTP-driven feeds to a modern lakehouse with Delta Sharing, Reader Accounts, or Fabric External Sharing — collapses the path from "data exists somewhere" to "agentic AI workflows can safely run against it." You're the person who decides what that target state looks like, defends those choices in front of a customer CTO, and then leads the team that builds it on a 10-week greenfield clock. You'll lead a tight bench of platform-specialist Senior Data Engineers (one each on Databricks, Snowflake, and Fabric) plus a Cloud/Platform Engineer. You're the public face of the practice in pre-sales discovery — and during active delivery, you're the engagement-embedded tech lead. Strong opinions, loosely held. Equally comfortable in a CTO conversation and a Terraform repo. This posting spans both Staff and Principal levels; the offer level is calibrated to depth of experience and breadth of demonstrated technical leadership. 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 - Serve as the engagement-embedded tech lead on the active engagement: architecture, design reviews, and hands-on build on the hardest parts - Lead 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. - Required 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 IDEAL EXPERIENCE - 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 te