Director of Data Engineering and Analytics

Greenbrook Medical • New York City, NY

1d • Hybrid

About The Position

Greenbrook Medical is seeking its first dedicated data leader to build the company's foundational data layer and data intelligence capabilities. This hands-on role involves daily coding, owning production systems from day one, and developing a roadmap for data infrastructure and business logic. The position requires forecasting needs, building a data team and culture, and ensuring end-to-end ownership from platform to metric delivery and team performance. The Director will report to the VP of Growth and Population Health and collaborate with care teams to enhance the observability of the care model. Key responsibilities include owning the analytics layer (dbt models, business logic, metric definitions), managing reporting and BI, taking ownership of production systems (including uptime and integrity), and developing a data capabilities roadmap and team. The role is hybrid in New York City, with flexibility for exceptional remote candidates.

Requirements

• Strong SQL, dbt, and Python, and still write production code.
• Hands-on experience with healthcare data, including claims, eligibility, and EHR data.
• Familiarity with interoperability standards such as FHIR and HL7.
• Experience with value-based care measurement, such as HEDIS/Stars, HCC/RAF, and utilization.
• Ability to interpret data and explain it to clinical and business leaders in plain language.
• Experience owning production systems, including responding when something breaks.
• Experience building roadmaps, driving alignment on them, and hiring technical talent.
• A bachelor's degree.
• A mindset grounded in core values of Heart, Excellence, Accountability, Resilience, and Teamwork.

Nice To Haves

• Experience at a risk-bearing organization (ACO, MA plan, at-risk provider), especially where data powered internal clinical software.
• Tie data to workflow: moved a quality measure, not just reported on it.
• Challenge the status quo constructively.
• Get to root cause: find out why a number is wrong instead of patching the symptom.
• Enjoy both hardening what exists and building what's next.
• Are AI-native: use modern AI tools in daily work.
• Drive outcomes: bias for action and close loops without being chased.

Responsibilities

• Own the Analytics Layer: Build and maintain dbt models and business logic, ensure consistent metric definitions across all platforms.
• 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 engineering partner into steady state, improve them, catch and resolve ingestion, pipeline, and logic issues within SLAs, build monitoring and uptime reporting, and act as the production counterpart for the engineering partner.
• 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 within clinical workflows, participate in operating meetings where data is used, define what should be measured and what good looks like, and surface patterns and risks proactively.
• Build the roadmap and the team: Own the end-to-end data roadmap, construct quarterly roadmaps aligned with business needs, build the data team from scratch, define a people roadmap with sub-competencies and levels, and hire and manage data engineers and analysts, starting as a player-coach.

Benefits

• Competitive base salary: Remote (U.S.): $160,000–$190,000; New York City: $175,000–$210,000
• Generous annual performance bonus
• Health, dental, and vision insurance
• Paid time off
• 401(k) with company match

What This Job Offers

• Job Type: Full-time
• Career Level: Director