Director, Data Modernization

Qualified Health PBC

2d•$165,000 - $200,000•Hybrid

About The Position

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. The Director of Data Modernization is the technical architect and engineering leader across all of Qualified Health's data modernization engagements. You'll walk into a health system's data environment — which might be anything from a well-maintained EHR reporting database to a tangle of flat files and manual SFTP processes — and design the modern cloud data platform that will replace it. This is the highest-leverage work on the team. Every health system you modernize from legacy connectivity to a modern data sharing pattern reduces their ongoing integration effort dramatically. You're not just building infrastructure — you're removing the single biggest bottleneck to AI deployment across our entire partner base. You'll own the technical architecture playbook, make design decisions across concurrent engagements, lead a team of data engineers and cloud/infrastructure engineers, review all engineering output, and personally drive the most complex builds. The Engagement Manager handles the partner relationship and project management — you handle the engineering. Together, you run the engagement.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related field.
6+ years in data engineering or data platform roles, with demonstrated technical leadership
Deep Azure expertise: Databricks, ADLS2, Azure networking, managed identities, Terraform/Bicep
Experience with data platform design and deployment (greenfield builds)
Client-facing experience — comfortable leading technical conversations with health system IT teams

Nice To Haves

A Master's degree is preferred.
Familiarity with EHR data sources and clinical data models (Epic Clarity/Caboodle preferred)
Experience with data sharing protocols (Delta Share, Fabric External Sharing, or similar)
Background in consulting, professional services, or data platform implementation
Experience designing data architectures for HIPAA-regulated environments
Track record of managing technical quality across concurrent engagements
Architectural Judgment: You can walk into an unfamiliar data environment, assess what exists, identify what's missing, and design a target state architecture that is both technically sound and achievable within a time-boxed engagement
Hands-On Leadership: You lead by example — reviewing code, pairing with engineers on tough problems, and shipping your own work alongside the team
Pragmatism: You know the difference between "architecturally ideal" and "what we can actually deliver in the engagement window" — and you optimize for the latter without creating technical debt
Client Presence: You're comfortable in a room with a health system CIO or VP of IT, explaining technical decisions in business terms
Documentation: You maintain engagement playbooks and architecture patterns so the next engagement benefits from what you learned in the last one

Responsibilities

Own the technical architecture for modernization engagements: Azure Databricks design, data landing zones, networking, security controls
Lead and develop a team of data engineers and cloud/infrastructure engineers
Lead technical discovery and source data assessments for new engagements
Review and approve all engineering deliverables across concurrent engagements
Personally drive architecture and build for the most complex engagements
Set engineering quality standards and drive architectural decisions across the modernization practice
Maintain and evolve the technical engagement playbook
Ensure environments meet handoff criteria for the Client Integration team
Collaborate with Data Mapping Analysts on source data assessment and validation