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Non-cloud data engineering is horrible, if you are talking about building on-prem data lakes and doing advanced analytics/on-prem spark and Hadoop etc - extremely painful and limited access to some of the game changing services on public cloud (like machine vision, NLP, textract etc.).
Both are in high demand so it really matters more which you enjoy, you can also do some combination of both (Cloud engineering with a specialization on data platforms, the certifications tracks even support this e.g. AWS Certified Data Analytics - Specialty or Data engineering but building solutions on the hyperscalers).
What makes it horrible/painful?
Chief
You sound like you’re more interested in the data engineering role
Sounds like you can’t go wrong then. Decide based on team, WLB, salary.
data engineering / even if it is non-cloud, you can move later into cloud based data engineering since it would be a good transition. If you chose cloud engineering, then that is a different branch altogether, would be hard to transition back to data engineering