diff --git a/python_src/src/lamp_py/aws/s3.py b/python_src/src/lamp_py/aws/s3.py
index f7f9aecc..9eadb0c4 100644
--- a/python_src/src/lamp_py/aws/s3.py
+++ b/python_src/src/lamp_py/aws/s3.py
@@ -20,7 +20,7 @@
 import boto3
 import pandas
 import pyarrow
-import pyarrow.dataset as ds
+import pyarrow.compute as pc
 import pyarrow.parquet as pq
 from pyarrow import Table, fs
 from pyarrow.util import guid
@@ -336,7 +336,8 @@ def write_parquet_file(
     @s3_dir - the s3 bucket plus prefix "subdirectory" path where the
         parquet files should be written
     @partition_cols - column names in the table to partition out into the
-        filepath.
+        filepath. NOTE: the assumption is that the values in the partition
+        columns of the incoming table are uniform.
     @visitor_func - if set, this function will be called with a WrittenFile
         instance for each file created during the call. a WrittenFile has
         path and metadata attributes.
@@ -349,26 +350,34 @@ def write_parquet_file(
     )
     process_logger.log_start()
 
-    # generate partitioning for this table write based on what columns
-    # we expect to be able to partition out for this input type
-    partitioning = ds.partitioning(
-        table.select(partition_cols).schema, flavor="hive"
-    )
+    # pull out the partition information into a list of strings.
+    partition_strings = []
+    for col in partition_cols:
+        unique_list = pc.unique(table.column(col)).to_pylist()
+        assert len(unique_list) == 1
+        partition_strings.append(f"{col}={unique_list[0]}")
+
+    table = table.drop(partition_cols)
 
+    # generate an s3 path to write this file to
     if basename_template is None:
         basename_template = guid() + "-{i}.parquet"
-
-    ds.write_dataset(
-        data=table,
-        base_dir=s3_dir,
-        filesystem=fs.S3FileSystem(),
-        format=ds.ParquetFileFormat(),
-        partitioning=partitioning,
-        file_visitor=visitor_func,
-        basename_template=basename_template,
-        existing_data_behavior="overwrite_or_ignore",
+    write_path = os.path.join(
+        s3_dir, *partition_strings, basename_template.format(i=0)
     )
 
+    process_logger.add_metadata(write_path=write_path)
+
+    # write teh parquet file to the partitioned path
+    with pq.ParquetWriter(
+        where=write_path, schema=table.schema, filesystem=fs.S3FileSystem()
+    ) as pq_writer:
+        pq_writer.write(table)
+
+    # call the visitor function if it exists
+    if visitor_func is not None:
+        visitor_func(write_path)
+
     process_logger.log_complete()