video1.0<iframe src="https://www.loom.com/embed/c738fccc4f394cb9afdb7aba243ce347" frameborder="0" width="1280" height="960" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>9601280Loomhttps://www.loom.com9601280https://cdn.loom.com/sessions/thumbnails/c738fccc4f394cb9afdb7aba243ce347-0bfd1d69927147dd.gif69This Loom explains the approach to interviewing and evaluating data engineering candidates. The speaker says they first study the basics of the role, such as what data engineering is, to form better questions. They prefer situational and specific questions, for example asking a hiring manager about current business problems and then exploring how the candidate solves a complex data engineering problem. They also use AI to identify what a mid-level data engineer should know and compare that with business needs to assess fit.