Senior Data Platform Engineer

Healthcare's helping hand.

CHG shook things up in 1979 by inventing the locum tenens staffing model.

We connect doctors with patients who need their care.

As the largest physician staffing firm in America, our providers treat millions of patients each year.

Our industry is growing and demand is high.

This means you'll have plenty of opportunities to grow and develop in your career.

Keeping healthcare healthy can be as fun as it is rewarding

CareerMD is evolving the foundation of its platform to support faster product development and more intelligent, data-driven experiences for physicians and employers.

We operate a platform that facilitates recruitment and practice-finding between physicians and organizations that employ them.

Today, this platform relies on a shared data store.

While it has supported the business well, we are now investing in a more flexible, scalable approach that enables cleaner system boundaries, improved data quality, and stronger product capabilities across the platform.

We are beginning by rebuilding an existing application, including a newly refactored application-specific DB, as the first step in a broader, domain-oriented data architecture.

This work is not limited to a single application.

It will establish the patterns, models, and data flows that will be extended across multiple systems over time.

This foundation will support:

• clean system boundaries

• reliable data flows

• canonical identity and profiles

• behavioral data and feedback loops

• AI-enabled product capabilities

Over time, this data layer will allow us to turn fragmented data into intelligence, and to build a compounding advantage in how we match physicians and employers.

We are looking for a Founding Senior Data Platform Engineer to own and build this layer.

This is not a traditional data role.

You will define how data works across the company.

This role will report to the VP of Product and Engineering.

Responsibilities:


* Decompose a monolithic MySQL system into domain-oriented data stores.

Define data ownership and source-of-truth boundaries.

Establish data contracts between systems.

Partner with engineering to implement pragmatic, incremental migration paths.


* Design and implement pipelines for employer, job, and physician data.

Define and maintain canonical entities and schemas.

Solve identity resolution and deduplication across fragmented sources.


* Design event tracking and behavioral data models.

Enable cross-system visibility into user behavior.

Support use cases such as matching and recommendations, funnel optimization, and employer-physician engagement.


* Structure data for AI, ML, and LLM-based workflows.

Build pipelines that support enrichment, ranking and matching, and feedback loops.

Help define how AI integrates into product experiences.


* Work directly with our engineering team and Product Manager.

Use AI tools to accelerate development and decision-making.

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