[00:02] someone else's work, and that someone usually earns more. A data scientist with bad data is just an expensive guesser. Somebody has to collect it from 10 messy places, clean it, and deliver it on time every single day. That's the
[00:15] data engineer. Think of a restaurant. The scientist is the chef plating the fancy dish, and the engineer built the kitchen, runs the supply, and keeps the gas on. If the engineers pipelines break, the scientists cannot work. The
[00:29] market agrees. There are around 85,000 active data engineer postings in the US against about 52,000 for data scientists, and engineers earn roughly 8 to 15% more at every level. Meanwhile, interview activity for data scientist
[00:45] interview activity for data scientist roles fell 56% between September 2025 and June 2026. So, which one fits you? If you like without anyone noticing, go data
[00:57] engineering. If you like testing ideas and asking, "What if?" go data science.