diff --git a/ibis/backends/snowflake/__init__.py b/ibis/backends/snowflake/__init__.py
index d62b98de5178..05fa65d7827f 100644
--- a/ibis/backends/snowflake/__init__.py
+++ b/ibis/backends/snowflake/__init__.py
@@ -365,62 +365,63 @@ def _register_in_memory_table(self, op: ops.InMemoryTable) -> None:
 
         from ibis.backends.snowflake.datatypes import to_sqla_type
 
-        t = op.data.to_pyarrow(schema=op.schema)
         dialect = self.con.dialect
         quote = dialect.preparer(dialect).quote_identifier
-        table = quote(op.name)
-        stage = util.gen_name("stage")
+        raw_name = op.name
+        table = quote(raw_name)
 
         with self.begin() as con:
-            # 1. create a temporary stage for holding parquet files
-            con.exec_driver_sql(f"CREATE TEMP STAGE {stage}")
-
-            with tempfile.TemporaryDirectory(ignore_cleanup_errors=True) as tmpdir:
-                path = os.path.join(tmpdir, f"{op.name}.parquet")
-                # optimize for bandwidth so use zstd which typically compresses
-                # better than the other options without much loss in speed
-                pq.write_table(t, path, compression="zstd")
-
-                # 2. copy the parquet file into the stage
-                #
-                # disable the automatic compression to gzip because we've
-                # already compressed the data with zstd
-                #
-                # 99 is the limit on the number of threads use to upload data,
-                # who knows why?
+            if con.exec_driver_sql(f"SHOW TABLES LIKE '{raw_name}'").scalar() is None:
+                # 1. create a temporary stage for holding parquet files
+                stage = util.gen_name("stage")
+                con.exec_driver_sql(f"CREATE TEMP STAGE {stage}")
+
+                with tempfile.TemporaryDirectory(ignore_cleanup_errors=True) as tmpdir:
+                    t = op.data.to_pyarrow(schema=op.schema)
+                    path = os.path.join(tmpdir, f"{raw_name}.parquet")
+                    # optimize for bandwidth so use zstd which typically compresses
+                    # better than the other options without much loss in speed
+                    pq.write_table(t, path, compression="zstd")
+
+                    # 2. copy the parquet file into the stage
+                    #
+                    # disable the automatic compression to gzip because we've
+                    # already compressed the data with zstd
+                    #
+                    # 99 is the limit on the number of threads use to upload data,
+                    # who knows why?
+                    con.exec_driver_sql(
+                        f"""
+                        PUT 'file://{path}' @{stage}
+                        PARALLEL = {min((os.cpu_count() or 2) // 2, 99)}
+                        AUTO_COMPRESS = FALSE
+                        """
+                    )
+
+                # 3. create a temporary table
+                schema = ", ".join(
+                    "{name} {typ}".format(
+                        name=quote(col),
+                        typ=sa.types.to_instance(to_sqla_type(dialect, typ)).compile(
+                            dialect=dialect
+                        ),
+                    )
+                    for col, typ in op.schema.items()
+                )
+                con.exec_driver_sql(f"CREATE TEMP TABLE {table} ({schema})")
+                # 4. copy the data into the table
+                columns = op.schema.names
+                column_names = ", ".join(map(quote, columns))
+                parquet_column_names = ", ".join(f"$1:{col}" for col in columns)
                 con.exec_driver_sql(
                     f"""
-                    PUT 'file://{path}' @{stage}
-                    PARALLEL={min((os.cpu_count() or 2) // 2, 99)}
-                    AUTO_COMPRESS=FALSE
+                    COPY INTO {table} ({column_names})
+                    FROM (SELECT {parquet_column_names} FROM @{stage})
+                    FILE_FORMAT = (TYPE = PARQUET COMPRESSION = AUTO)
+                    PURGE = TRUE
                     """
                 )
 
-            # 3. create a temporary table
-            schema = ", ".join(
-                "{name} {typ}".format(
-                    name=quote(col),
-                    typ=sa.types.to_instance(to_sqla_type(dialect, typ)).compile(
-                        dialect=dialect
-                    ),
-                )
-                for col, typ in op.schema.items()
-            )
-            con.exec_driver_sql(f"CREATE TEMP TABLE {table} ({schema})")
-
-            # 4. copy the data into the table
-            columns = op.schema.names
-            column_names = ", ".join(map(quote, columns))
-            parquet_column_names = ", ".join(f"$1:{col}" for col in columns)
-            con.exec_driver_sql(
-                f"""
-                COPY INTO {table} ({column_names})
-                FROM (SELECT {parquet_column_names} FROM @{stage})
-                FILE_FORMAT=(TYPE=PARQUET COMPRESSION=AUTO)
-                PURGE=TRUE
-                """
-            )
-
     def _get_temp_view_definition(
         self, name: str, definition: sa.sql.compiler.Compiled
     ) -> str:
diff --git a/ibis/backends/snowflake/tests/test_client.py b/ibis/backends/snowflake/tests/test_client.py
index bfa495af4f26..c11da4465ffe 100644
--- a/ibis/backends/snowflake/tests/test_client.py
+++ b/ibis/backends/snowflake/tests/test_client.py
@@ -55,3 +55,19 @@ def test_basic_memtable_registration(simple_con, data):
     t = ibis.memtable(data)
     result = simple_con.execute(t)
     tm.assert_frame_equal(result, expected)
+
+
+def test_repeated_memtable_registration(simple_con, mocker):
+    data = {"key": list("abc"), "value": [[1], [2], [3]]}
+    expected = pd.DataFrame(data)
+    t = ibis.memtable(data)
+
+    spy = mocker.spy(simple_con, "_register_in_memory_table")
+
+    n = 2
+
+    for _ in range(n):
+        tm.assert_frame_equal(simple_con.execute(t), expected)
+
+    # assert that we called _register_in_memory_table exactly n times
+    assert spy.call_count == n