I published the 2026 State of Data Engineering Survey with findings from 1,101 data professionals. But I'm certain there are patterns in the data I didn't see.

That's where you come in.

The Challenge

Analyze the survey data and surface an insight that isn't in the published report.

Maybe it's a cross-tabulation I didn't think to run. A regional pattern. A correlation between org size and some unexpected variable. A better way to visualize a finding. Anything that makes someone say "huh, that's interesting."

Examples of what you might find:

• Data engineers in Europe have different problems than their American counterparts…and what about everywhere else in the world?
• Company size vs AI hiring, AI usage, etc
• A hidden relationship between team size and tech stack complexity

How to Enter

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Four simple steps:

1. Explore the data: Use the Survey Explorer — filter, crosstab, run SQL, or download the CSV
2. Find something interesting: An insight, pattern, or visualization not in the report
3. Share it publicly: Post on LinkedIn or Twitter/X with the hashtag #PracticalDataSurvey
4. Tag me: So I can find it (@josephreis on LinkedIn)

That's it. No forms. No submissions portal. Just post your finding.

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Timeline

Prizes

🏆 Best Insight

The most surprising or useful finding that wasn't in the original report.