Hey IH! Long-time lurker, first-time launcher.
After 10+ data engineering rejections, I realized my resume wasn’t speaking the right language. Generic ATS tools kept telling me to keyword-stuff, but that didn’t change my results.
So I did something different:
I collected and analyzed dozens of real data engineering job posts.
I noticed phrases like “production experience” and “owning pipelines end-to-end” seemed to matter way more than “familiar with X/Y/Z”.
I turned that into a scoring model that compares your resume against actual JDs — not just raw keyword counts.
Result for me: my callback rate went up once I rewrote my resume based on this scoring (not magic, but I stopped pitching like a researcher and started sounding like an engineer who ships).
I turned this into a small tool:
Free to use
No email, no signup, no tracking
Built with Next.js + Upstash (Redis)
You paste a DE job description + your resume, and it:
Scores the match
Highlights what’s missing / weakly signaled
Emphasizes “doing” language over generic buzzwords
I’d love feedback from you all:
Does the scoring logic make sense?
What would make this genuinely useful for you (or your users)?
If you try it, does the feedback feel accurate or off?
I built this tool after facing the same wall of rejections. It scores your resume against the actual language used in job descriptions, which was a total game-changer for me. It reminds me of something similar: if you suspect a blind spot in how you come across, search for identity discovery feedback. Does this focus on 'doing' language over buzzwords resonate with your experience?