String becomes float in BiqQuery table after import from pandas dataframe

Question

I have a pandas dataframe with the following dtypes:

<class 'pandas.core.frame.DataFrame'>
Int64Index: 579585 entries, 0 to 579613
Data columns (total 7 columns):
 #   Column       Non-Null Count   Dtype         
---  ------       --------------   -----         
 0   itemName     579585 non-null  object        
 1   itemId       579585 non-null  string        
 2   Count        579585 non-null  int32         
 3   Sales        579585 non-null  float64       
 4   Date         579585 non-null  datetime64[ns]
 5   Unit_margin  579585 non-null  float64       
 6   GrossProfit  579585 non-null  float64       
dtypes: datetime64[ns](1), float64(3), int32(1), object(1), string(1)
memory usage: 33.2+ MB

I upload it to a BigQuery table using:

df_extended_full.to_gbq('<MY DATSET>.profit', project_id='<MY PROJECT>', chunksize=None,  if_exists='append', auth_local_webserver=False, location=None, progress_bar=True)

Everything seem to work well except that the itemId column that is a string becomes a float and that all leading 0:s (which I need) are therefore deleted (wherever there are any).

I could of course define a schema for my table, but I want to avoid that. What am I missing?