As woodward said you would have to read the data as it is and clean it with regular expressions, see this example (Obviously not a complete solution because honestly, this is going to be a little tedious)
library(tidyverse)
sample_data <- readLines("Sample.txt")
sample_data %>%
enframe(name = NULL) %>%
filter(str_detect(value, "^\\d{2}-")) %>%
separate(value, sep = "\\s+", into = c("cert_id", "cust_id", "sites"))
#> Warning: Expected 3 pieces. Additional pieces discarded in 9 rows [1, 2, 3, 4,
#> 5, 6, 7, 8, 9].
#> # A tibble: 9 x 3
#> cert_id cust_id sites
#> <chr> <chr> <chr>
#> 1 10-C-6666 503768 1
#> 2 11-A-5555 17234 1
#> 3 11-B-4444 67 2
#> 4 15-C-2222 32000 1
#> 5 19-C-9999 322900 1
#> 6 14-C-0000 323000 1
#> 7 19-C-1111 7890 1
#> 8 14-C-0045 4356 1
#> 9 11-C-2356 7345 1