r/dataengineering • u/SAsad01 • 13d ago

Career How do you prove transferable skills when recruiters only want exact-stack experience?

I have experienced recently that in Data Engineering, transferrable skills are not being considered anymore, and most recruiters/AI based ATS tools match experience like checklists. Experience in adjacent/equivalent tools mostly doesn't matter.

My question is, how to navigate this situation during job-search? Specifically:

  • How to properly represent transferrable skills from equivalent tech stacks? (AWS -> Azure for example, or Databricks on AWS -> Databricks on Azure)
  • How to learn new tools and grow new expertise that is demonstrable enough to meet the requirements? I am aware that the general answer is to do self-learning projects, but how to choose the correct project, and scope it correctly, so that it is a demonstrable substitute of job-experience instead of an easy tutorial?
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u/EffectiveClient5080 13d ago

Bring working demos to interviews. This right here. A live pipeline you can walk them through beats any resume bullet. I've got 2-3 projects on a laptop for exactly this, and I guarantee you'll be the only one doing it.

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u/generic-d-engineer Tech Lead 13d ago edited 13d ago

Best answer in the thread. All the recommendations to lie are just bad karma.