Analytics Engineer

Thatch is rewiring how health benefits work. We build software that gives employees real control over how they use their benefits.

We're looking for an Analytics Engineer to own the data models, metrics, and dashboards the company runs on. You'll define how we measure the business, from source data through the numbers that leadership, growth, finance, and operations use every day. This work touches real money and real healthcare decisions. Consistency and reliability matter, but so does making the data simple to use for the teams who depend on it.

• Take ownership of meaningful metrics and data products, from definition through adoption.
• Build and maintain dbt models that define how we measure the business.
• Design and maintain dashboards used by growth, finance, and operations to make day-to-day decisions.
• Improve data quality through testing, monitoring, and validation.
• Enable self-serve analytics so teams can answer their own questions and move faster.

• Experience building analytics models and dashboards in a production environment.
• Strong SQL skills and experience with dbt or similar tools, and working knowledge of python for ad-hoc analysis.
• Strong intuition for metric design, including grain, aggregation, and edge cases.
• Eagerness to work closely with stakeholders to define problems and translate them into metrics, models, and analytic tools.
• Good judgment when balancing speed, accuracy, and maintainability.

We hire across levels and care most about the scope you’ve owned, the impact you’ve had, and how you make decisions.

• dbt and SQL for modeling.
• Snowflake as our data warehouse (migrating from Redshift).
• Omni for BI, with tools like Hex for ad hoc analysis.
• GitHub with CI/CD for version control.
• AI tools (e.g., Claude, ChatGPT, Copilot) are woven into our daily development and analysis workflow.

You won’t work directly in our application layer day-to-day, but understanding source data from systems like Ruby on Rails is important.

• Experience with data testing, CI/CD, and building reliable, observable data systems.
• Partnering closely with finance, growth, or go-to-market teams.
• Building self-serve analytics tools that reduce ad hoc requests.
• Working in healthcare, fintech, or other complex, regulated domains.

• We move quickly and are biased toward action.
• We ship early, learn from real usage, and iterate.
• We operate with trust, ownership, and high empathy.
• We value clarity over ceremony and quality over shortcuts.

We aim to move quickly, and most candidates complete the process within 2–3 weeks. You can expect:

• An initial conversation with a recruiter.
• A conversation with the hiring manager.
• A take-home analytics exercise.
• A review of your work, including modeling and coding exercises with the team, and a discussion with cross-functional partners.
• A final conversation with engineering and company leadership.