dplyr: mutate_at + coalesce: dynamic names of columns

Guess it is now possible to achieve the desired outcome using mutate + across

data_example %>% 
  mutate(across(c(str_subset(names(.), "_extra") %>% str_remove("_extra")) ,
                ~ coalesce( ., get(str_c(cur_column(), "_extra"))  ))) 

  aa bb cc aa_extra bb_extra
1  1  1  6        2        1
2  2  2  7        2        2
3 NA  2  8       NA        3

We can split the dataset into a list of data.frames after removing the substring of column names ("_extra"), then with map loop through the list, coalesce the column and then bindwith the "_extra" columns in the original dataset

library(tidyverse)
data_example %>% 
   split.default(str_remove(names(.), "_extra")) %>%
   map_df(~ coalesce(!!! .x)) %>%
   #or use
   # map_df(reduce, coalesce) %>%
   bind_cols(., select(data_example, ends_with("extra")))
# A tibble: 3 x 5
#     aa    bb    cc aa_extra bb_extra
#  <dbl> <dbl> <dbl>    <dbl>    <dbl>
#1     1     1     6        2        1
#2     2     2     7        2        2
#3    NA     2     8       NA        3