diff --git a/sdk/python/feast/infra/offline_stores/contrib/spark_offline_store/spark.py b/sdk/python/feast/infra/offline_stores/contrib/spark_offline_store/spark.py
index b81ca5ab1bb..f1ba4baa939 100644
--- a/sdk/python/feast/infra/offline_stores/contrib/spark_offline_store/spark.py
+++ b/sdk/python/feast/infra/offline_stores/contrib/spark_offline_store/spark.py
@@ -497,10 +497,18 @@ def to_remote_storage(self) -> List[str]:
                 return aws_utils.list_s3_files(
                     self._config.offline_store.region, output_uri
                 )
-
+            elif self._config.offline_store.staging_location.startswith("hdfs://"):
+                output_uri = os.path.join(
+                    self._config.offline_store.staging_location, str(uuid.uuid4())
+                )
+                sdf.write.parquet(output_uri)
+                spark_session = get_spark_session_or_start_new_with_repoconfig(
+                    store_config=self._config.offline_store
+                )
+                return _list_hdfs_files(spark_session, output_uri)
             else:
                 raise NotImplementedError(
-                    "to_remote_storage is only implemented for file:// and s3:// uri schemes"
+                    "to_remote_storage is only implemented for file://, s3:// and hdfs:// uri schemes"
                 )
 
         else:
@@ -629,6 +637,22 @@ def _list_files_in_folder(folder):
     return files
 
 
+def _list_hdfs_files(spark_session: SparkSession, uri: str) -> List[str]:
+    jvm = spark_session._jvm
+    jsc = spark_session._jsc
+    if jvm is None or jsc is None:
+        raise RuntimeError("Spark JVM or JavaSparkContext is not available")
+    conf = jsc.hadoopConfiguration()
+    path = jvm.org.apache.hadoop.fs.Path(uri)
+    fs = jvm.org.apache.hadoop.fs.FileSystem.get(path.toUri(), conf)
+    statuses = fs.listStatus(path)
+    files = []
+    for f in statuses:
+        if f.isFile():
+            files.append(f.getPath().toString())
+    return files
+
+
 def _cast_data_frame(
     df_new: pyspark.sql.DataFrame, df_existing: pyspark.sql.DataFrame
 ) -> pyspark.sql.DataFrame: