AI-Driven Data Modernization Lead (Healthcare)

Qualified Health; United States; On-site; USD 130,000 - 165,000; Full time

Benefits offered by this job

Equity

Hybrid work options

Competitive salary

Job summary

Qualified Health seeks an Engagement Manager for Data Modernization to lead delivery lifecycle across our health-system partners, guiding modern Azure Databricks environments and cloud-native architectures to deploy agentic AI workflows.

You will own scope, milestones, and handoffs, coordinate across engineering, mapping, and infrastructure, and maintain partner relationships while managing risks and timelines.

Qualifications

• 4–7 years in technical project/program management or professional services delivery.
• Experience with data platforms, cloud infrastructure, or data integration projects.
• Fluent with Azure, Databricks, data pipelines, and networking basics.
• Strong communication for status reports and risk escalation.
• Willingness to travel 20–30% for on-site engagements.

Responsibilities

• Own the modernization engagement lifecycle from scoping to handoff to integration.
• Serve as primary contact for partner stakeholders during engagements.
• Coordinate across engineering, data mapping, cloud/infrastructure, and client teams.
• Manage timelines, risks, and dependencies for 2–3 concurrent engagements.
• Lead weekly status calls with partner teams.
• Ensure smooth handoff to the Client Integration team after modernization.
• Develop and refine the engagement playbook for repeatability and scale.
• Monitor resource capacity and flag conflicts early.

Skills

Technical project management

Azure Databricks

Data pipelines

Communication

Travel readiness

Education

Bachelor's degree in Engineering, Business, Information Technology, or a related field

Tools

Azure

Databricks

Terraform

GitHub Actions

Python

Job description

Qualified Health seeks an Engagement Manager for Data Modernization to lead delivery lifecycle across our health-system partners, guiding modern Azure Databricks environments and cloud-native architectures to deploy agentic AI workflows.

You will own scope, milestones, and handoffs, coordinate across engineering, mapping, and infrastructure, and maintain partner relationships while managing risks and timelines.