diff --git a/daft/table/table_io.py b/daft/table/table_io.py
index 0f892534d9..f540d7ced6 100644
--- a/daft/table/table_io.py
+++ b/daft/table/table_io.py
@@ -672,9 +672,12 @@ def __call__(self, written_file):
             else:
                 size = 0
 
+            # remove leading slash
+            path = written_file.path[1:] if written_file.path.startswith("/") else written_file.path
+
             self.parent.add_actions.append(
                 AddAction(
-                    written_file.path,
+                    path,
                     size,
                     self.partition_values,
                     int(datetime.now().timestamp() * 1000),
diff --git a/src/daft-parquet/src/lib.rs b/src/daft-parquet/src/lib.rs
index 039124e4a2..76fe734ee0 100644
--- a/src/daft-parquet/src/lib.rs
+++ b/src/daft-parquet/src/lib.rs
@@ -27,7 +27,7 @@ pub enum Error {
 
     #[snafu(display("Parquet reader timed out while trying to read: {path} with a time budget of {duration_ms} ms"))]
     FileReadTimeout { path: String, duration_ms: i64 },
-    #[snafu(display("Internal IO Error when Opening: {path}:\nDetails:\n{source}"))]
+    #[snafu(display("Internal IO Error when opening: {path}:\nDetails:\n{source}"))]
     InternalIOError {
         path: String,
         source: std::io::Error,
diff --git a/tests/io/delta_lake/test_table_write.py b/tests/io/delta_lake/test_table_write.py
index 7a65d835cb..03d84571b1 100644
--- a/tests/io/delta_lake/test_table_write.py
+++ b/tests/io/delta_lake/test_table_write.py
@@ -300,3 +300,13 @@ def test_deltalake_write_partitioned_existing_table(tmp_path):
     assert result["rows"] == [1, 1]
 
     check_equal_both_daft_and_delta_rs(df1.concat(df2), path, [("int", "ascending"), ("string", "ascending")])
+
+
+def test_deltalake_write_roundtrip(tmp_path):
+    path = tmp_path / "some_table"
+    df = daft.from_pydict({"a": [1, 2, 3, 4]})
+    df.write_deltalake(str(path))
+
+    read_df = daft.read_deltalake(str(path))
+    assert df.schema() == read_df.schema()
+    assert df.to_arrow() == read_df.to_arrow()