Assuming your list is called list_df, you can bind them all together using bind_rows, group_by date and then sum all the other columns.
library(dplyr)
list_df %>%
bind_rows() %>%
group_by(date) %>%
summarise_all(sum)
# A tibble: 3 x 3
# date clicks impressions
#
#1 2019-06-01 3 16
#2 2019-06-02 3 14
#3 2019-06-03 111 149
which in base R could be achieved using Reduce
aggregate(.~date, Reduce(rbind, list_df), sum)
