Data Engineer, Analytics

About the role

As a Data Engineer, you'll play a foundational role in shaping the data infrastructure, models, and pipelines that power our growth and revenue dashboards, core analytics, and predictive modeling efforts. This is a hybrid role at the intersection of data infrastructure, analytics engineering, and business impact. You’ll architect reliable systems, model key business entities, and partner with teams across to unlock insights, all while laying the foundation for a data practice that scales. This is an ideal role for someone who thrives on technical ownership, moves fluidly between backend systems and product logic, and wants to help define how a company uses data from the ground up.

What you'll do

• Own and evolve modern data stack (Redshift, dbt, Fivetran, Dagster/Airflow, Metabase, Hex).
• Build reliable ELT pipelines to integrate internal systems and third-party APIs with strong observability and scale.
• Model core business logic (e.g., plan years, employer funding, engagement metrics) into scalable dbt models.
• Establish trust in data through monitoring, testing, and CI/CD best practices.
• Collaborate cross-functionally to support analytics, experimentation, and strategic decision-making.

Background we're looking for

• 3–5+ years of experience in data engineering, analytics engineering, or backend engineering with a data focus.
• Strong software engineering skills (Python preferred) with experience in modular pipelines and tooling.
• Advanced SQL and hands-on experience with dbt.
• Familiarity with orchestration tools (Airflow, Dagster, Prefect) and modern data warehouses (Redshift, Snowflake, BigQuery).
• Comfortable partnering cross-functionally with product, ops, and analytics.

Experience we’d be particularly excited about

• Prior experience building data platforms or analytics foundations in a fast-paced startup.
• Experience with CI/CD, data testing (e.g., dbt tests, Great Expectations), and data observability.
• Led or contributed to a cloud data warehouse migration (e.g., Redshift to Snowflake or BigQuery), including managing dbt model portability, cost/performance tuning, and coordination across teams.
• Previous work in the healthcare or fintech industries.

What to expect

We interview rigorously based on integrity, talent, and drive; the trust we display in our teammates from day 1 is a reflection of the confidence we have in this process. We aim to evaluate the things you’ll be doing every day as best we can, and we move quickly. Here's what to expect:

• 15 minute phone screen to talk through your background and interest in
• 30 minute Zoom meeting with the hiring manager to dive deeper into your experience and the role
• 30 minute Zoom meeting to meet 2-3 members of the team
• 30 minute Zoom meeting with the hiring manager to work through a live case study
• 30 minute Zoom meeting with our founders to discuss your approach to culture and our operating principles