diff --git a/src/hipscat_import/catalog/file_readers.py b/src/hipscat_import/catalog/file_readers.py
index af630e87..5a549737 100644
--- a/src/hipscat_import/catalog/file_readers.py
+++ b/src/hipscat_import/catalog/file_readers.py
@@ -291,18 +291,24 @@ class ParquetReader(InputReader):
         chunksize (int): number of rows of the file to process at once.
             For large files, this can prevent loading the entire file
             into memory at once.
+        column_names (list[str] or None): Names of columns to use from the input dataset.
+            If None, use all columns.
         kwargs: arguments to pass along to pyarrow.parquet.ParquetFile.
             See https://arrow.apache.org/docs/python/generated/pyarrow.parquet.ParquetFile.html
     """
 
-    def __init__(self, chunksize=500_000, **kwargs):
+    def __init__(self, chunksize=500_000, column_names=None, **kwargs):
         self.chunksize = chunksize
+        self.column_names = column_names
         self.kwargs = kwargs
 
     def read(self, input_file, read_columns=None):
         self.regular_file_exists(input_file, **self.kwargs)
+        columns = read_columns or self.column_names
         parquet_file = pq.ParquetFile(input_file, **self.kwargs)
-        for smaller_table in parquet_file.iter_batches(batch_size=self.chunksize, use_pandas_metadata=True):
+        for smaller_table in parquet_file.iter_batches(
+            batch_size=self.chunksize, columns=columns, use_pandas_metadata=True
+        ):
             yield smaller_table.to_pandas()
 
     def provenance_info(self) -> dict:
diff --git a/tests/hipscat_import/catalog/test_file_readers.py b/tests/hipscat_import/catalog/test_file_readers.py
index d7fd2a14..c7f76176 100644
--- a/tests/hipscat_import/catalog/test_file_readers.py
+++ b/tests/hipscat_import/catalog/test_file_readers.py
@@ -255,6 +255,19 @@ def test_parquet_reader_provenance_info(tmp_path, basic_catalog_info):
     io.write_provenance_info(catalog_base_dir, basic_catalog_info, provenance_info)
 
 
+def test_parquet_reader_columns(parquet_shards_shard_44_0):
+    """Verify we can read a subset of columns."""
+    column_subset = ["id", "dec"]
+
+    # test column_names class property
+    for frame in ParquetReader(column_names=column_subset).read(parquet_shards_shard_44_0):
+        assert set(frame.columns) == set(column_subset)
+
+    # test read_columns kwarg
+    for frame in ParquetReader().read(parquet_shards_shard_44_0, read_columns=column_subset):
+        assert set(frame.columns) == set(column_subset)
+
+
 def test_read_fits(formats_fits):
     """Success case - fits file that exists being read as fits"""
     total_chunks = 0