PySpark to rename a column in a dataframe

Hello. I am quite new to Spark Notebooks. I am using one to extract JSON data to save to tables in a Lakehouse. It works, but there are some slight issues. The data, being JSON, has nexted objects. I have included a screenshot here to highlight my issues.

I am starting with a data frame to read the entire JSON file. But the contents of the nested fields contain nested objects. So I have a second data frame that selects elements from the first using something like this:

df2 = df1.select( "Id", "EmployeeNumber",..."PositionData.Manager.Id"..."WorkLocation.Id"...)

But the second and third columns that are "Id" come out named "Id". I now have THREE columns named "Id" in the data frame. I want to rename the second and third ones to "Manager_Id" and "WorkLocation_Id", respectively.

I want to flatten the entire JSON file (there are no nested arrays, just nexted objects) such that I have the original Id (for the Employee) and Manager Id and Work Location Id. 

I tried data frame with Column Rename but it renames all column named Id.

If this was SQL I could write it as: select..."PositionData.Manager.Id" AS [Manager_Id]...

Is there a way to rename a column inline in a dataframe select operation? Or is there another/better option?

Thanks in advance