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What is the best folder organization for a large data analysis project with multilayered subprojects?

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My project involves several subprojects. They should be completed in a sequential manner. And each subproject involves different steps of data wrangling and analysis. Each step would produce intermediate data, which are needed for the next step. I have two folder tree design. I don't know which one is better. What would be potential pros and cons for each design?
The first tree design.
subproject 1
step 1 (code, data, figure, ...)
step 2 (code, data, figure, ...) uses data from step 1 as input and output new data
step N (code, data, figure, ...)
subproject 2, ..., subproject N
each has multiple steps and similar sub-folder-tree
The second tree design.
code (subproject 1 (step 1, step 2, ...), subproject 2 (step 1, step 2, ...) , ..., subproject N)
data (subproject 1 (step 1, step 2, ...), subproject 2 (step 1, step 2, ...), ..., subproject N)
figure (similar sub-tree pattern)

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