Data Engineer

This is a Data Engineer opportunity with a growing Series D US digital health business focused on making psychiatry more accessible through technology. The role sits within a growing data team and is aimed at someone past their first data engineering job who can ship reliably and work independently within a defined scope. The business operates at significant scale, with hundreds of psychiatrists and therapists and over two million patient visits delivered, so the pipelines you build feed analytics, operations and clinical reporting that the whole organisation relies on. You’ll build and maintain ingestion pipelines and Python services on AWS, develop dbt models in Snowflake with proper tests and documentation, and move scheduled tasks into Airflow DAGs. You’ll work closely with the BI and Analytics Engineering team to turn their needs into dependable data engineering work, contribute to CI/CD pipelines and team standards, take part in the on-call rotation and post-mortems, and mentor newer team members. The ideal candidate will have 2+ years’ experience as a data engineer or in a closely related role such as backend engineering with substantial data work or analytics engineering. Strong Python and advanced SQL are essential, along with experience on a cloud data warehouse (Snowflake preferred) and comfort working in AWS. dbt, Airflow, Fivetran or similar ETL tooling, and healthcare experience would all be advantageous. This is a fully remote US position suited to someone who enjoys owning their pipelines end to end and wants their work to have a visible effect on patient care.

Requirements