$ hire --advisory
Data Engineering Hiring Advisory
Helping teams hire data engineers who can actually build and operate production systems.
The Problem
Most resumes look good. Most interviews test the wrong things. Many teams end up hiring candidates who can talk about systems but struggle to build and operate them in production.
With 15+ years in the industry as a Principal Engineer, I've seen what works and what doesn't when it comes to building data teams.
What I Help With
Designing the Hiring Process
- Defining the right roles and seniority levels
- Writing realistic job descriptions
- Avoiding overbroad or misleading requirements
- Aligning expectations between engineering, data, and leadership
Interview Design & Calibration
- Designing interview loops for data engineers
- Creating practical, production-relevant exercises
- Evaluating trade-offs, not trivia
- Calibrating interviewers to reduce false positives and negatives
Candidate Evaluation
- Reviewing candidate profiles and experience
- Participating in technical interviews as an independent evaluator
- Providing structured feedback on strengths and risks
- Helping decide when to hire, pass, or level differently
Building the First Data Team
- Hiring the first senior or principal data engineer
- Avoiding early hires that lock you into bad architecture
- Structuring teams for growth, not just delivery
- Establishing engineering standards from day one
Common Problems This Solves
- "We keep hiring strong resumes but weak execution"
- "Interviews don't reflect the work we actually do"
- "We don't know how senior this candidate really is"
- "We need to hire our first data engineer and can't afford mistakes"
- "Our hiring bar is inconsistent across interviewers"
Want to discuss how to improve your hiring process?
/contact →