Data Engineer

About the Team

You'll join an early and growing data engineering team that's shaping the foundations of our data platform. We're investing in a modern transformation layer, reliable pipelines, and richer in-product analytics for our clients and you'll have real influence over how that gets built.

About the Role

You'll be one of the first data engineers on our team. This is hands-on, high-ownership work: building our transformation layer, strengthening our analytics pipelines, and creating the data models that power both internal reporting and the analytics our clients see inside the product.

What You’ll Do

• Build data models: develop dbt models and SQL transformations, backed by tests, that turn raw data into reliable datasets.
• Improve pipeline reliability: help monitor our replication and orchestrated pipelines, investigate data issues, and add quality checks.
• Power reporting: build and refine the datasets and dashboards that internal teams and clients rely on.
• Learn and grow: work closely with senior engineers, take part in code review, and steadily take on more ownership.

Who You Are

We're open on exact tools — we care about fundamentals and trajectory. You'll likely have most of the following:

• 3-5 years of professional data engineering experience
• Strong SQL: you write correct, readable SQL and understand relational data modeling
• Data experience: you've developed data pipelines and transformations in production environments
• Eagerness to learn: you take feedback well, ask good questions, and are excited to grow as a data engineer

Nice to have: exposure to dbt, CDC / replication or orchestration tools (e.g. Estuary Flow, Debezium/Kafka, Airflow), a cloud data warehouse (ex. Redshift), a BI tool (ex. Sigma, Looker); comfort with PostgreSQL or a similar database.

• Databases: PostgreSQL across our production and analytics environments, with room to grow into a cloud warehouse (ex. Redshift) as we scale
• Ingestion: CDC / streaming replication into analytics (evaluating tools like Estuary Flow and Debezium/Kafka)
• Transformation: building out a version-controlled, dbt-based staging/marts layer with data tests and CI/CD
• Orchestration: scheduled, observable pipeline runs (e.g. Airflow or similar)
• BI & embedded analytics: a modern BI and embedding platform (we use Sigma) for internal reporting and in-product client analytics, with a maturing semantic/metrics layer
• Domain: life sciences / healthcare data; comfort working in HIPAA-aware, PHI-handling environments is a plus

• 100% paid employee health benefit options (including medical, dental, and vision)
• 401(k) with employer funded match
• Unlimited Vacation
• Commuter Benefits
• Paid parental leave
• Catered lunch on Fridays
• Wellness stipend

The annual salary range for the target level for this role is $120,000-$150,000 + equity + benefits, including medical, dental, and vision. Final compensation will be determined based on a variety of factors including relevant experience, interview performance, and internal equity.