The Organizational State of Data Engineering

Three surveys in 2026. 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. Take the survey (https://docs.google.com/forms/d/e/1FAIpQLSdnMmRjCyLs4dRL6wGb3CMHWisVnl6r4VV1VaqiZr1AarEmFg/viewform?usp=dialog) Thank you for your support 🙏 Joe