Case Study · Specialist Engineering

Privacy Engineer

Client: Dandelion Health

Sourced entirely through outbound, not a job posting: 633 candidates over 92 days, closing at $140K total comp.

92 days
Search to hire
633
Candidates in the pipeline
Outbound
Sourced, not posted
$140K
Total comp

The requirement

Dandelion Health needed an engineer to build and operate de-identification pipelines protecting patient health information across more than 10 million patients' worth of structured, unstructured, imaging, and waveform data. 2+ years Python, working SQL and Bash.

The search

This one started as a direct outbound sourcing sequence, not a job posting, reaching out to specific candidates on LinkedIn before a single application came in. It ran to 633 candidates in the system before we closed it, 92 days start to finish.

Who we placed

An engineer who started their career at a large industrial technology company, building backend Java and Python microservices, including asynchronous batch-processing systems for claims data. They came in with hands-on AWS experience (CloudFormation, CodeBuild, CodePipeline, S3, CloudWatch) and, critically, real hands-on experience working with de-identified data, the exact skill this search was built around.

The outcome

Placed at $140K total comp. The first interview was a direct intro call with Dandelion Health's Head of Engineering, and we stayed engaged with the candidate through their first two weeks on the job to confirm a strong start.

Other documented searches

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