Why the Line Between Data Engineer and ML Engineer Is Disappearing, And Why That

<h2> Introduction: A Confusion That's Costing the Industry </h2> <p>Every week, someone posts a job description asking for an <strong>"ML Engineer"</strong> when they actually

<p>Lately, it feels like my feed is completely flooded with "Become an AI/ML Engineer in 2 Hours!" crash courses and quick certificates promising a golden fast-track into machine

<p>AI is getting better at writing code every month. I asked people in tech, on Reddit and in my own network, what comes next.</p> <p>Say you've just been hired by two clients in

<p>Every year, someone publishes a "State of Data Engineering" survey with 200 respondents, mostly from their own Slack community, and calls it representative. I ignore most of

<p>For decades, the tech industry chased the myth of the “10x Developer.” We looked for that rare unicorn who could out-code a small team. But today, that myth has been shattered

<p>Most candidates don’t fail data engineering interviews because of SQL or Python; they fail because they can’t connect everything together under pressure.</p> <p>If you’ve ever