Passing an optional data frame column to a custom function

I have a custom function that takes as input a data frame and then a selection of columns from that data frame, like this:

library(dplyr)
df <- data.frame(x = c(1, 2, 3, 4, 5), y = c(11, 12, 13, 14, 15))

sample_fun <- function(df, x, y) {
  df <- df %>% 
    mutate(z = {{x}} * {{y}})
  }

df_out <- sample_fun(df, x, y)

I'd like to make one of the data frame columns optional, and then have the function test for its presence using !if.null(). If this was an object, rather than a data frame column, I would do this:

sample_fun <- function(df, x, y = NULL) {
  if(!is.null(y)) {
    df <- df %>% 
      mutate(z = {{x}} * y)
  }
  else(df <- df %>%
         mutate(z = {{x}}))
}

df_out <- sample_fun(df, x) 
df_out2 <- sample_fun(df, x, y)

However, I can't figure out how to check for the presence of the data column. Both if(!is.null(y)) and if(!is.null({{y}})) return Error: object 'y' not found. What is the best way to check for the presence of y, when y is a data frame column rather than an independent object?

One option is to check if the y variable is missing, instead of using NULL as a placeholder.

sample_fun <- function(df, x, y) {
  if (!missing(y)) {
    df <- mutate(df, z = {{x}} * {{y}})
  } else {
    df <- mutate(df, z = {{x}})
  }
  return(df)
}
df_out <- sample_fun(df, x) 
df_out2 <- sample_fun(df, x, y)