diff --git a/awswrangler/s3/_read_parquet.py b/awswrangler/s3/_read_parquet.py
index e46a5a5a7..00d037d7c 100644
--- a/awswrangler/s3/_read_parquet.py
+++ b/awswrangler/s3/_read_parquet.py
@@ -2,6 +2,7 @@
 
 import concurrent.futures
 import datetime
+import functools
 import itertools
 import json
 import logging
@@ -339,8 +340,8 @@ def _read_parquet_chunked(
                     if next_slice is not None:
                         df = _union(dfs=[next_slice, df], ignore_index=ignore_index)
                     while len(df.index) >= chunked:
-                        yield df.iloc[:chunked]
-                        df = df.iloc[chunked:]
+                        yield df.iloc[:chunked, :].copy()
+                        df = df.iloc[chunked:, :]
                     if df.empty:
                         next_slice = None
                     else:
@@ -773,26 +774,32 @@ def read_parquet_table(
         path: str = res["Table"]["StorageDescriptor"]["Location"]
     except KeyError as ex:
         raise exceptions.InvalidTable(f"Missing s3 location for {database}.{table}.") from ex
-    return _data_types.cast_pandas_with_athena_types(
-        df=read_parquet(
-            path=path,
-            path_suffix=filename_suffix,
-            path_ignore_suffix=filename_ignore_suffix,
-            partition_filter=partition_filter,
-            columns=columns,
-            validate_schema=validate_schema,
-            categories=categories,
-            safe=safe,
-            map_types=map_types,
-            chunked=chunked,
-            dataset=True,
-            use_threads=use_threads,
-            boto3_session=boto3_session,
-            s3_additional_kwargs=s3_additional_kwargs,
-        ),
-        dtype=_extract_partitions_dtypes_from_table_details(response=res),
+    df = read_parquet(
+        path=path,
+        path_suffix=filename_suffix,
+        path_ignore_suffix=filename_ignore_suffix,
+        partition_filter=partition_filter,
+        columns=columns,
+        validate_schema=validate_schema,
+        categories=categories,
+        safe=safe,
+        map_types=map_types,
+        chunked=chunked,
+        dataset=True,
+        use_threads=use_threads,
+        boto3_session=boto3_session,
+        s3_additional_kwargs=s3_additional_kwargs,
+    )
+    partial_cast_function = functools.partial(
+        _data_types.cast_pandas_with_athena_types, dtype=_extract_partitions_dtypes_from_table_details(response=res)
     )
 
+    if isinstance(df, pd.DataFrame):
+        return partial_cast_function(df)
+
+    # df is a generator, so map is needed for casting dtypes
+    return map(partial_cast_function, df)
+
 
 @apply_configs
 def read_parquet_metadata(