Our largest funnel: 884 candidates screened over 105 days, closing at $150K total comp.
A software engineer to build and operate de-identification pipelines removing protected health information from clinical data, at real scale. 3+ years of professional Python, comfortable in AWS and SQL-based warehouses (Snowflake, Redshift), Pandas, Docker.
The largest funnel we've documented: 884 candidates, most of them inbound applications, narrowed down through screening to a small qualified slate and one hire. This was the longest search of the group, 105 days, reflecting how specific the data-privacy engineering requirement was.
An engineer with roughly eight years building data-intensive applications and ETL systems, most recently as the sole developer owning data ingestion, processing, and analytics workflows involving sensitive healthcare claims data. Before that, four-plus years building cloud-based Python microservices supporting large-scale ETL pipelines, at times processing up to 12 terabytes of data over three-month windows.
Placed at $150K total comp, through an interview loop with Dandelion Health's Head of Data, a coding assessment, and executive interviews. This search was run as a genuine team effort across three Beacon recruiters.
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