Just solved this myself using pyspark with dbutils to get the .csv and rename to the wanted filename.
save_location= "s3a://landing-bucket-test/export/"+year
csv_location = save_location+"temp.folder"
file_location = save_location+'export.csv'
df.repartition(1).write.csv(path=csv_location, mode="append", header="true")
file = dbutils.fs.ls(csv_location)[-1].path
dbutils.fs.cp(file, file_location)
dbutils.fs.rm(csv_location, recurse=True)
This answer can be improved by not using [-1], but the .csv seems to always be last in the folder. Simple and fast solution if you only work on smaller files and can use repartition(1) or coalesce(1).