Job Summary: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.
Key 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
- This role requires travel to healthcare client sites for engagement kickoffs, technical discovery sessions, and key milestones. Candidates should be prepared for 15-25% travel, depending on active engagements.
Required Qualifications:- Education: Bachelor's degree in Computer Science, Engineering, or a related field. A Master's degree is preferred.
- Required Experience:
- 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
Preferred Skills:- 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
Technical Environment:Our data infrastructure is built on modern cloud technologies including:
- Azure Databricks + Data Factory (plus Fabric and Snowflake integrations)
- PySpark for distributed data processing
- GitHub Actions + Terraform for CI/CD and Infrastructure as Code
- Python with type-safe patterns and modern frameworks
- Healthcare data formats including FHIR, Epic Clarity, and other EHR schemas
Pay & Benefits: The pay range for this role is between $165,000 and $200,000, and will depend on your skills, qualifications, experience, and location. This role is also eligible for equity and benefits.
Join our mission to revolutionize healthcare with AI. To apply, please send your resume through the application below.
