If you’ve worked in data engineering over the last few years, you’ve probably encountered — the extract-and-load platform that helped popularize the "ELT" approach before it became standard.

Before Stitch, many teams wrote custom Python/Scala extraction scripts. Stitch (and tools like Fivetran) made extraction a commodity. Today’s data engineers spend less time dealing with API rate limits or pagination — and more time on modeling, governance, and quality.

Here’s a concise, professional LinkedIn post about Stitch as a data integration platform in the context of modern data engineering. Stitch, Data Integration, and the State of Data Engineering

Here’s what Stitch got right (and what it means for data engineers today):