diff --git a/integration_tests/src/main/python/parquet_test.py b/integration_tests/src/main/python/parquet_test.py
index 6032d469fb2..7d041b387e4 100644
--- a/integration_tests/src/main/python/parquet_test.py
+++ b/integration_tests/src/main/python/parquet_test.py
@@ -485,6 +485,8 @@ def test_parquet_read_buffer_allocation_empty_blocks(spark_tmp_path, v1_enabled_
             lambda spark : spark.read.parquet(data_path).filter("id < 2 or id > 990"),
             conf=all_confs)
 
+
+@disable_ansi_mode  # https://github.com/NVIDIA/spark-rapids/issues/5114
 @pytest.mark.parametrize('reader_confs', reader_opt_confs)
 @pytest.mark.parametrize('v1_enabled_list', ["", "parquet"])
 @pytest.mark.skipif(is_databricks_runtime(), reason="https://github.com/NVIDIA/spark-rapids/issues/7733")
@@ -797,6 +799,8 @@ def test_parquet_read_nano_as_longs_true(std_input_path):
         'FileSourceScanExec',
         conf=conf)
 
+
+@disable_ansi_mode  # https://github.com/NVIDIA/spark-rapids/issues/5114
 def test_many_column_project():
     def _create_wide_data_frame(spark, num_cols):
         schema_dict = {}
@@ -1285,27 +1289,64 @@ def test_parquet_read_case_insensitivity(spark_tmp_path):
     )
 
 
-# test read INT32 as INT8/INT16/Date
-@pytest.mark.parametrize('reader_confs', reader_opt_confs)
-@pytest.mark.parametrize('v1_enabled_list', ["", "parquet"])
-def test_parquet_int32_downcast(spark_tmp_path, reader_confs, v1_enabled_list):
+def run_test_parquet_int32_downcast(spark_tmp_path,
+                                    reader_confs,
+                                    v1_enabled_list,
+                                    ansi_conf):
+    """
+    This tests whether Parquet files with columns written as INT32 can be
+    read as having INT8, INT16 and DATE columns, with ANSI mode enabled/disabled.
+    """
     data_path = spark_tmp_path + '/PARQUET_DATA'
     write_schema = [("d", date_gen), ('s', short_gen), ('b', byte_gen)]
+
+    # For test setup, write with ANSI disabled.
+    # Otherwise, CAST(d AS INT) will fail on Spark CPU.
     with_cpu_session(
         lambda spark: gen_df(spark, write_schema).selectExpr(
             "cast(d as Int) as d",
             "cast(s as Int) as s",
-            "cast(b as Int) as b").write.parquet(data_path))
+            "cast(b as Int) as b").write.parquet(data_path), conf=ansi_disabled_conf)
 
     read_schema = StructType([StructField("d", DateType()),
                               StructField("s", ShortType()),
                               StructField("b", ByteType())])
     conf = copy_and_update(reader_confs,
-                           {'spark.sql.sources.useV1SourceList': v1_enabled_list})
+                           {'spark.sql.sources.useV1SourceList': v1_enabled_list},
+                           ansi_conf)
     assert_gpu_and_cpu_are_equal_collect(
         lambda spark: spark.read.schema(read_schema).parquet(data_path),
         conf=conf)
 
+
+@pytest.mark.parametrize('reader_confs', reader_opt_confs)
+@pytest.mark.parametrize('v1_enabled_list', ["", "parquet"])
+def test_parquet_int32_downcast_ansi_disabled(spark_tmp_path, reader_confs, v1_enabled_list):
+    """
+    This tests whether Parquet files with columns written as INT32 can be
+    read as having INT8, INT16 and DATE columns, with ANSI mode disabled.
+    """
+    run_test_parquet_int32_downcast(spark_tmp_path,
+                                    reader_confs,
+                                    v1_enabled_list,
+                                    ansi_disabled_conf)
+
+
+def test_parquet_int32_downcast_ansi_enabled(spark_tmp_path):
+    """
+    This is the flipside of test_parquet_int32_downcast_ansi_disabled.
+    This tests whether Parquet files with columns written as INT32 can be
+    read as having INT8, INT16 and DATE columns, now tested with ANSI
+    enabled.
+    A limited combination of test parameters is used to test ANSI enabled,
+    in the interest of brevity.
+    """
+    run_test_parquet_int32_downcast(spark_tmp_path,
+                                    reader_confs=native_parquet_file_reader_conf,
+                                    v1_enabled_list="",
+                                    ansi_conf=ansi_disabled_conf)
+
+
 @pytest.mark.parametrize('reader_confs', reader_opt_confs)
 @pytest.mark.parametrize('v1_enabled_list', ["", "parquet"])
 @pytest.mark.parametrize("types", [("byte", "short"), ("byte", "int"), ("short", "int")], ids=idfn)
@@ -1340,6 +1381,10 @@ def test_parquet_nested_column_missing(spark_tmp_path, reader_confs, v1_enabled_
         lambda spark: spark.read.schema(read_schema).parquet(data_path),
         conf=conf)
 
+@pytest.mark.skipif(condition=is_databricks_runtime() and is_databricks_version_or_later(14,3),
+                    reason="https://github.com/NVIDIA/spark-rapids/issues/11512")
+@pytest.mark.skipif(condition=is_spark_400_or_later(),
+                    reason="https://github.com/NVIDIA/spark-rapids/issues/11512")
 def test_parquet_check_schema_compatibility(spark_tmp_path):
     data_path = spark_tmp_path + '/PARQUET_DATA'
     gen_list = [('int', int_gen), ('long', long_gen), ('dec32', decimal_gen_32bit)]
@@ -1431,13 +1476,16 @@ def test_parquet_read_encryption(spark_tmp_path, reader_confs, v1_enabled_list):
     assert_spark_exception(
         lambda: with_gpu_session(
             lambda spark: spark.read.parquet(data_path).collect()),
-        error_message='Could not read footer for file')
+        error_message='Could not read footer')  # Common message fragment between all Spark versions.
+                                                # Note that this isn't thrown explicitly by the plugin.
 
     assert_spark_exception(
         lambda: with_gpu_session(
             lambda spark: spark.read.parquet(data_path).collect(), conf=conf),
         error_message='The GPU does not support reading encrypted Parquet files')
 
+
+@disable_ansi_mode  # https://github.com/NVIDIA/spark-rapids/issues/5114
 def test_parquet_read_count(spark_tmp_path):
     parquet_gens = [int_gen, string_gen, double_gen]
     gen_list = [('_c' + str(i), gen) for i, gen in enumerate(parquet_gens)]