About The RoleWe'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 DoOwn 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 escalate 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 the care model well enough to define what we should measure and what good looks like
- Surface patterns and risks proactively, acting as an early warning system for the business
Build the roadmap and the team
- Own the end-to-end data roadmap, from data strategy to product delivery and integration. Construct roadmaps on the order of quarters that align with what the business needs
- Build the data team from scratch. Put together a people roadmap, define sub-competencies based off of our needs, and design levels and competencies
- Hire and manage data engineers and analysts. Start as a player coach and then hire to supplement skills and ensure delivery against the roadmap
What Success Looks Like- Data trust: the business trusts the numbers, and you're ahead of issues rather than behind them
- Impact: data changes how we deliver care, and our quality measures improve year over year
- Early warning: leaders hear about emerging problems from you first
- Coverage: every metric our operating levers depend on has a certified definition and a single source of truth
- Reliability: systems transitioned to you stay healthy and get fixed fast when they break
- Scale readiness: new clinics come online with full data coverage from day one
- Delivery: committed quarterly work ships, and your counterparts, including performance managers and the Head of Population Health, rate the partnership highly
About YouYou bring:
- Strong SQL, dbt, and Python, and you still write production code
- Hands-on experience with healthcare data, including claims, eligibility, and EHR data and familiarity with interoperability standards such as FHIR and HL7
- Experience with value-based care measurement, such as HEDIS/Stars, HCC/RAF, and utilization
- The ability to interpret data and explain what it means to clinical and business leaders in plain language
- Experience owning production systems, including being the person who responds when something breaks
- Experience building roadmaps, driving alignment on them, and hiring technical talent
- A bachelor's degree
- A mindset grounded in our core values of Heart, Excellence, Accountability, Resilience, and Teamwork
You'll stand out if you:
- Have done this at a risk-bearing organization, such as an ACO, MA plan, or at-risk provider, especially where data powered internal clinical software
- Tie data to workflow: you've moved a quality measure, not just reported on it
- Challenge the status quo constructively: you'll tell us what's not working and why
- Get to root cause: you 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: you use modern AI tools in your daily work
- Drive outcomes: you have a bias for action and close loops without being chased
Strong, Transparent Compensation & 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
Our Selection ProcessApplication → Initial interview → Skills/experience interview → Values interview → Case Study and Case Study Interview → References
