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Director of Data Engineering and Analytics

Job in New York, New York County, New York, 10261, USA
Listing for: Greenbrook Medical
Full Time position
Listed on 2026-10-10
Job specializations:
  • IT/Tech
    Data Engineering, Business Intelligence
Salary/Wage Range or Industry Benchmark: 180000 - 260000 USD Yearly USD 180000.00 260000.00 YEAR
Job Description & How to Apply Below
Director of Data Engineering and Analytics

New York City, NY

About Us

Greenbrook Medical is building the new standard in primary care.

We deliver high-touch, relationship-based care through neighborhood clinics, grounded in a simple belief: every senior deserves the kind of care we would want for our own families. Our model prioritizes time with patients, strong care coordination, and a personalized approach that improves outcomes while lowering total cost of care.

We take full accountability for patient outcomes and overall cost of care, aligning clinical excellence with disciplined execution. That commitment shows up in our results, including a patient Net Promoter Score of 90, compared to 32 for typical healthcare organizations.

Rooted in Tampa Bay and partnered with Tampa General Hospital, we are entering an exciting phase of growth. Backed by strong unit economics, experienced operators, and a proven playbook, we are looking for builders and operators who want to help scale a healthcare platform designed to deliver better care, better coordination, and better outcomes for seniors.

About The Role

We're hiring our first dedicated data leader. You'll build Greenbrook's foundational data layer and data intelligence capabilities. You’ll also build our data team and culture from the ground up.

This is a hands on role. You'll be in the code daily, own what's in production from day one, and build the roadmap from scratch, inclusive of data infrastructure and business logic. You will forecast needs out on the magnitude of quarters and build a team to support delivery.

Success in this role means end to end ownership, from data platform to metric delivery and data team performance. You report to the VP of Growth and Population Health and partner closely with our care teams to improve observability on our care model.

As Greenbrook’s Head of Data & Analytics, you own four things:

  • The analytics layer
    : the dbt models and business logic that turn raw data into something usable, and the metric definitions underneath them
  • Reporting and BI
    : the reporting layer the whole business reads from, and turning data into findings that our teams can react on to improve performance
  • Our production systems
    : you take ownership of systems as they come in-house from our engineering partner, harden them, and keep making them better, with accountability for uptime & system integrity
  • The data roadmap and team development
    :
    You will develop, in partnership with Greenbrook’s functional leaders, a data capabilities roadmap that supports the business. You will translate that roadmap into tactical goals and hiring plans to ensure that the data team is improving observability across all aspects of the business.

Location: New York City strongly preferred (Hybrid). Open to exceptional remote candidates.

What You'll Do

Own the Analytics Layer

  • Build and maintain the dbt models and business logic behind our metrics and workflows in Google Cloud
  • Ensure metric definitions are consistent across every surface at Greenbrook
  • Build the reporting and dashboards the business uses to make decisions

Take Ownership of What's in Production

  • Take on systems as they move from our engineering partner into steady state, and keep improving them.
  • Catch ingestion, pipeline, and logic issues, and resolve them within our SLAs. Build monitoring and uptime reporting.
  • Be the counterpart our engineering partner hands production work to. Resolve what you can and elevate what needs them.

Make the Care Model Better With Data

  • Calculate and report on industry-standard care model measures
  • Turn quality and care-gap logic into triggers and flags inside our clinical workflows, so we act on data during the encounter, not after
  • Sit in the operating meetings where data gets used. Understand…
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