Analytics Engineer
Own data models, metrics, and dashboards that leadership, growth, finance, and operations rely on. Build dbt models, design BI dashboards, and enable self-serve analytics in a production environment.
What you will do
- 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.
What we are looking for
- 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.
Tools and tech stack
- 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.
Experience that stands out
- 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.
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