diff --git a/python/tests/test_merge.py b/python/tests/test_merge.py
index efec90900a..3e1ccc8a7e 100644
--- a/python/tests/test_merge.py
+++ b/python/tests/test_merge.py
@@ -2297,3 +2297,81 @@ def test_merge(tmp_path: pathlib.Path):
 
     new_df = pl.read_delta(str(tmp_path))
     assert_frame_equal(df, new_df, check_row_order=False)
+
+
+@pytest.mark.pyarrow
+@pytest.mark.pandas
+def test_merge_file_pruning_regression_3636(tmp_path: pathlib.Path):
+    """
+    https://github.com/delta-io/delta-rs/issues/3636
+    """
+    import pyarrow as pa
+    import pandas as pd
+    import numpy as np
+    import deltalake
+    from deltalake import DeltaTable
+
+    # create table once
+    dt = DeltaTable.create(
+        tmp_path,
+        pa.schema(
+            [
+                pa.field("ts", pa.timestamp("us"), nullable=False),
+                pa.field("direction", pa.string(), nullable=False),  # S, W, N, E
+                pa.field("distance", pa.float64(), nullable=False),
+                pa.field("updated_on", pa.int64(), nullable=False),  # timestamp in ms
+                pa.field("date", pa.string(), nullable=False),
+            ]
+        ),
+        partition_by=["date"],
+        mode="ignore",
+    )
+
+    def mock_data(size: int):
+        tss = pd.date_range(start="2025-01-01", freq="2s", periods=size // 4)
+
+        init_upd_df = {
+            "ts": [*tss] * 4,
+            "direction": [i for i in ("S", "W", "N", "E") for _ in range(len(tss))],
+            "distance": np.random.randint(0, 10000, size=len(tss) * 4),
+            "updated_on": list(
+                (tss.floor("D") + pd.Timedelta(hours=25)).astype(int) // 1000000
+            )
+            * 4,
+            "date": list(tss.strftime("%Y-%m-%d")) * 4,
+        }
+        return pd.DataFrame(init_upd_df)
+
+    # Let's prefill the table large enough to spread the results across
+    # multiple files
+    init_df = mock_data(500_000)
+
+    dt = DeltaTable(tmp_path)
+
+    dt.merge(
+        init_df,
+        predicate="s.date = t.date and s.ts = t.ts and s.direction = t.direction",
+        source_alias="s",
+        target_alias="t",
+    ).when_not_matched_insert_all().execute()
+
+    second_upd = mock_data(40)
+
+    dt = DeltaTable(tmp_path)
+
+    stats = (
+        dt.merge(
+            second_upd,
+            predicate="s.date = t.date and s.ts = t.ts and s.direction = t.direction",
+            source_alias="s",
+            target_alias="t",
+        )
+        .when_not_matched_insert_all()
+        .execute()
+    )
+
+    files_scanned = stats["num_target_files_scanned"]
+
+    assert files_scanned <= 1, (
+        f"The number of target files scanned was too large! {files_scanned}"
+    )