The Organizational State of Data Engineering
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Hey everyone! I did three surveys so far in 2026, and 1,629 data professionals responded. One consistent theme: data engineering’s challenges are mostly organizational, and that’s the top bottleneck in data work.
In January, “leadership direction” and “poor requirements” combined for 40% of top-bottleneck votes, well ahead of legacy systems at 25%. In April, 50% of practitioners named “lack of clear ownership” as a top pain point, well ahead of better tooling at under 5%.
So what does “lack of leadership direction” actually look like at your company? Who owns the data products and infrastructure? How do requirements arrive - written spec, Slack DM, or reverse-engineered from a broken dashboard? Is AI making your organization function better, or worse?
The new survey takes about a minute. Anonymous. A handful of questions. The dataset will be open to the public when it closes, like all the others.
Survey closes Sunday, June 21 at 11:59pm PT. Findings published the following week.
Thank you for your support 🙏
Joe