diff --git a/src/preset_cli/cli/superset/sync/dbt/datasets.py b/src/preset_cli/cli/superset/sync/dbt/datasets.py
index c0bf047..0484a14 100644
--- a/src/preset_cli/cli/superset/sync/dbt/datasets.py
+++ b/src/preset_cli/cli/superset/sync/dbt/datasets.py
@@ -3,7 +3,9 @@
 """
 
 # pylint: disable=consider-using-f-string
+from __future__ import annotations
 
+import copy
 import json
 import logging
 from typing import Any, Dict, List, Optional, Tuple
@@ -17,7 +19,7 @@
 from preset_cli.api.operators import OneToMany
 from preset_cli.cli.superset.sync.dbt.lib import create_engine_with_check
 from preset_cli.exceptions import CLIError, SupersetError
-from preset_cli.lib import raise_cli_errors
+from preset_cli.lib import dict_merge, raise_cli_errors
 
 DEFAULT_CERTIFICATION = {"details": "This table is produced by dbt"}
 
@@ -171,6 +173,7 @@ def compute_metrics(
     dbt_metrics: List[Any],
     reload_columns: bool,
     merge_metadata: bool,
+    metric_defaults: Dict[str, Any] | None = None,
 ) -> List[Any]:
     """
     Compute the final list of metrics that should be used to update the dataset
@@ -187,9 +190,13 @@ def compute_metrics(
 
     for name, metric_definition in model_metrics.items():
         if reload_columns or merge_metadata or name not in current_dataset_metrics:
+            final_metric = {}
             if name in current_dataset_metrics:
                 metric_definition["id"] = current_dataset_metrics[name]["id"]
-            final_dataset_metrics.append(metric_definition)
+            if metric_defaults:
+                final_metric = copy.deepcopy(metric_defaults)
+                dict_merge(final_metric, metric_definition)
+            final_dataset_metrics.append(final_metric or metric_definition)
 
     # Preserving Superset metadata
     if not reload_columns:
@@ -197,6 +204,9 @@ def compute_metrics(
             if not merge_metadata or name not in model_metrics:
                 # remove data that is not part of the update payload
                 metric = clean_metadata(metric)
+                if merge_metadata and metric_defaults:
+                    final_metric = copy.deepcopy(metric_defaults)
+                    dict_merge(metric, final_metric)
                 final_dataset_metrics.append(metric)
 
     return final_dataset_metrics
@@ -233,6 +243,7 @@ def compute_columns_metadata(
     dataset_columns: List[Any],
     reload_columns: bool,
     merge_metadata: bool,
+    column_defaults: Dict[str, Any] | None = None,
 ) -> List[Any]:
     """
     Adds dbt metadata to dataset columns.
@@ -251,6 +262,10 @@ def compute_columns_metadata(
         dbt_metadata[column]["verbose_name"] = column
         for key, value in definition.pop("meta", {}).get("superset", {}).items():
             dbt_metadata[column][key] = value
+        if column_defaults:
+            final_column = copy.deepcopy(column_defaults)
+            dict_merge(final_column, dbt_metadata[column])
+            dbt_metadata[column] = final_column
 
     for column in dataset_columns:
         name = column["column_name"]
@@ -258,6 +273,9 @@ def compute_columns_metadata(
             for key, value in dbt_metadata[name].items():
                 if reload_columns or merge_metadata or not column.get(key):
                     column[key] = value
+        elif column_defaults and (reload_columns or merge_metadata):
+            for key, value in column_defaults.items():
+                column[key] = value
 
         # remove data that is not part of the update payload
         column = clean_metadata(column)
@@ -338,12 +356,17 @@ def sync_datasets(  # pylint: disable=too-many-locals, too-many-arguments
             failed_datasets.append(model["unique_id"])
             continue
 
+        default_configs = (
+            model.get("meta", {}).get("superset", {}).pop("default_configs", {})
+        )
+
         # compute metrics
         final_dataset_metrics = compute_metrics(
             dataset["metrics"],
             metrics.get(model["unique_id"], []),
             reload_columns,
             merge_metadata,
+            metric_defaults=default_configs.get("metrics", {}),
         )
 
         # compute columns
@@ -387,6 +410,7 @@ def sync_datasets(  # pylint: disable=too-many-locals, too-many-arguments
                 current_dataset_columns,
                 reload_columns,
                 merge_metadata,
+                column_defaults=default_configs.get("columns", {}),
             )
             try:
                 client.update_dataset(
diff --git a/tests/cli/superset/sync/dbt/datasets_test.py b/tests/cli/superset/sync/dbt/datasets_test.py
index bea6c40..93bb169 100644
--- a/tests/cli/superset/sync/dbt/datasets_test.py
+++ b/tests/cli/superset/sync/dbt/datasets_test.py
@@ -376,12 +376,14 @@ def test_sync_datasets_custom_certification(mocker: MockerFixture) -> None:
         metrics[model_id],
         True,
         False,
+        metric_defaults={},
     )
     compute_columns_metadata_mock.assert_called_with(
         models[0]["columns"],
         client.get_dataset()["columns"],
         True,
         False,
+        column_defaults={},
     )
     compute_columns_mock.assert_not_called()
     compute_dataset_metadata_mock.assert_called_with(
@@ -529,12 +531,14 @@ def test_sync_datasets_external_url_disallow_edits(mocker: MockerFixture) -> Non
         metrics[model_id],
         True,
         False,
+        metric_defaults={},
     )
     compute_columns_metadata_mock.assert_called_with(
         models[0]["columns"],
         client.get_dataset()["columns"],
         True,
         False,
+        column_defaults={},
     )
     compute_columns_mock.assert_not_called()
     compute_dataset_metadata_mock.assert_called_with(
@@ -603,12 +607,14 @@ def test_sync_datasets_preserve_metadata(mocker: MockerFixture) -> None:
         metrics[model_id],
         False,
         False,
+        metric_defaults={},
     )
     compute_columns_metadata_mock.assert_called_with(
         models[0]["columns"],
         client.get_dataset()["columns"],
         False,
         False,
+        column_defaults={},
     )
     compute_columns_mock.assert_called_with(
         get_or_create_dataset_mock()["columns"],
@@ -682,12 +688,14 @@ def test_sync_datasets_merge_metadata(mocker: MockerFixture) -> None:
         metrics[model_id],
         False,
         True,
+        metric_defaults={},
     )
     compute_columns_metadata_mock.assert_called_with(
         models[0]["columns"],
         client.get_dataset()["columns"],
         False,
         True,
+        column_defaults={},
     )
     compute_columns_mock.assert_called_with(
         get_or_create_dataset_mock()["columns"],
@@ -762,6 +770,7 @@ def test_sync_datasets_no_columns(mocker: MockerFixture) -> None:
         metrics[model_id],
         True,
         False,
+        metric_defaults={},
     )
     compute_columns_mock.assert_not_called()
     compute_dataset_metadata_mock.assert_called_with(
@@ -1132,6 +1141,214 @@ def test_compute_metrics_without_merge_and_reload_no_metrics() -> None:
     assert result == metrics["model.superset_examples.messages_channels"]
 
 
+def test_compute_metrics_with_default_configs() -> None:
+    """
+    Test the ``compute_metrics`` helper with ``default_configs`` and
+    ``reload_columns`` set to ``True`` and ``merge_metadata`` to `False`.
+
+    dbt metrics should be synced
+    Superset metrics should be discarded
+    """
+    dbt_metrics: Dict[str, List[SupersetMetricDefinition]] = {
+        "model.superset_examples.messages_channels": [
+            {
+                "description": "Description from dbt",
+                "expression": "COUNT(*)",
+                "extra": "{}",
+                "metric_name": "cnt",
+                "metric_type": "count",
+                "verbose_name": "",
+            },
+            {
+                "expression": "COUNT(*)",
+                "extra": "{}",
+                "metric_name": "cnt_new",
+                "metric_type": "count",
+                "verbose_name": "",
+            },
+        ],
+    }
+    superset_metric = [
+        {
+            "description": "Superset desc",
+            "expression": "SUM(price_each)",
+            "metric_name": "revenue",
+            "id": 2,
+            "verbose_name": "SUM from Superset",
+        },
+    ]
+
+    result = compute_metrics(
+        superset_metric,
+        dbt_metrics["model.superset_examples.messages_channels"],
+        True,
+        False,
+        metric_defaults={"description": "default desc"},
+    )
+    assert result == [
+        {
+            "description": "Description from dbt",
+            "expression": "COUNT(*)",
+            "extra": "{}",
+            "metric_name": "cnt",
+            "metric_type": "count",
+            "verbose_name": "",
+        },
+        {
+            "description": "default desc",
+            "expression": "COUNT(*)",
+            "extra": "{}",
+            "metric_name": "cnt_new",
+            "metric_type": "count",
+            "verbose_name": "",
+        },
+    ]
+
+
+def test_compute_metrics_with_default_configs_merge_metadata() -> None:
+    """
+    Test the ``compute_metrics`` helper with ``default_configs`` and
+    ``reload_columns`` set to ``False`` and ``merge_metadata`` to `True`.
+
+    dbt metrics are synced
+    Superset-only metadata is kept
+    """
+    dbt_metrics: Dict[str, List[SupersetMetricDefinition]] = {
+        "model.superset_examples.messages_channels": [
+            {
+                "description": "Description from dbt",
+                "expression": "COUNT(*)",
+                "extra": "{}",
+                "metric_name": "cnt",
+                "metric_type": "count",
+                "verbose_name": "",
+            },
+            {
+                "expression": "COUNT(*)",
+                "extra": "{}",
+                "metric_name": "cnt_new",
+                "metric_type": "count",
+                "verbose_name": "",
+            },
+        ],
+    }
+    superset_metric = [
+        {
+            "description": "Superset desc",
+            "expression": "SUM(price_each)",
+            "metric_name": "revenue",
+            "id": 2,
+            "verbose_name": "SUM from Superset",
+        },
+    ]
+
+    result = compute_metrics(
+        superset_metric,
+        dbt_metrics["model.superset_examples.messages_channels"],
+        False,
+        True,
+        metric_defaults={"description": "default desc"},
+    )
+
+    assert result == [
+        {
+            "description": "Description from dbt",
+            "expression": "COUNT(*)",
+            "extra": "{}",
+            "metric_name": "cnt",
+            "metric_type": "count",
+            "verbose_name": "",
+        },
+        {
+            "description": "default desc",
+            "expression": "COUNT(*)",
+            "extra": "{}",
+            "metric_name": "cnt_new",
+            "metric_type": "count",
+            "verbose_name": "",
+        },
+        {
+            "description": "default desc",
+            "expression": "SUM(price_each)",
+            "metric_name": "revenue",
+            "id": 2,
+            "verbose_name": "SUM from Superset",
+        },
+    ]
+
+
+def test_compute_metrics_with_default_configs_preserve_metadata() -> None:
+    """
+    Test the ``compute_metrics`` helper with default_configs and
+    both ``reload_columns`` and ``merge_metadata`` set to ``False``.
+
+    dbt metrics are synced
+    Superset-only metadata is kept
+    """
+    dbt_metrics: Dict[str, List[SupersetMetricDefinition]] = {
+        "model.superset_examples.messages_channels": [
+            {
+                "description": "Description from dbt",
+                "expression": "COUNT(*)",
+                "extra": "{}",
+                "metric_name": "cnt",
+                "metric_type": "count",
+                "verbose_name": "",
+            },
+            {
+                "expression": "COUNT(*)",
+                "extra": "{}",
+                "metric_name": "cnt_new",
+                "metric_type": "count",
+                "verbose_name": "",
+            },
+        ],
+    }
+    superset_metric = [
+        {
+            "description": "Superset desc",
+            "expression": "SUM(price_each)",
+            "metric_name": "revenue",
+            "id": 2,
+            "verbose_name": "SUM from Superset",
+        },
+    ]
+
+    result = compute_metrics(
+        superset_metric,
+        dbt_metrics["model.superset_examples.messages_channels"],
+        False,
+        False,
+        metric_defaults={"description": "default desc"},
+    )
+
+    assert result == [
+        {
+            "description": "Description from dbt",
+            "expression": "COUNT(*)",
+            "extra": "{}",
+            "metric_name": "cnt",
+            "metric_type": "count",
+            "verbose_name": "",
+        },
+        {
+            "description": "default desc",
+            "expression": "COUNT(*)",
+            "extra": "{}",
+            "metric_name": "cnt_new",
+            "metric_type": "count",
+            "verbose_name": "",
+        },
+        {
+            "description": "Superset desc",
+            "expression": "SUM(price_each)",
+            "metric_name": "revenue",
+            "id": 2,
+            "verbose_name": "SUM from Superset",
+        },
+    ]
+
+
 def test_compute_columns_no_new_columns(mocker: MockerFixture) -> None:
     """
     Test the ``compute_columns`` helper when no new columns are returned.
@@ -1326,6 +1543,111 @@ def test_compute_columns_metadata_dbt_column_meta() -> None:
     assert result == expected
 
 
+def test_compute_columns_metadata_with_default_configs() -> None:
+    """
+    Test the ``compute_columns_metadata`` helper with ``default_configs`` and
+    ``reload_columns`` set to ``True`` and ``merge_metadata`` to `False`.
+
+    dbt metrics should be synced
+
+    Running it with ``reload_columns`` set to ``False`` and ``merge_metadata``
+    to `True` should produce the same result, as we don't discard column metadata.
+    """
+    default_column_config = {"filterable": False, "description": "dbt desc"}
+    model_columns = [{"name": "id", "description": "Primary key"}]
+    dataset_columns = [
+        {
+            "advanced_data_type": None,
+            "changed_on": "2024-01-23T20:29:33.945074",
+            "column_name": "product_line",
+            "created_on": "2024-01-23T20:29:33.945070",
+            "description": "Description for Product Line",
+            "expression": None,
+            "extra": "{}",
+            "filterable": True,
+            "groupby": True,
+            "id": 1,
+            "is_active": True,
+            "is_dttm": False,
+            "python_date_format": None,
+            "type": None,
+            "type_generic": None,
+            "uuid": "5b0dc14a-8c1a-4fcb-8791-3a955d8609d3",
+            "verbose_name": None,
+        },
+        {
+            "advanced_data_type": None,
+            "changed_on": "2024-01-03T13:30:19.139128",
+            "column_name": "id",
+            "created_on": "2021-12-22T16:59:38.825689",
+            "description": "Description for ID",
+            "expression": None,
+            "extra": "{}",
+            "filterable": True,
+            "groupby": False,
+            "id": 2,
+            "is_active": None,
+            "is_dttm": False,
+            "python_date_format": None,
+            "type": "INTEGER",
+            "type_generic": None,
+            "uuid": "a2952680-2671-4a97-b608-3483cf7f11d2",
+            "verbose_name": None,
+        },
+    ]
+    expected = [
+        {
+            "advanced_data_type": None,
+            "column_name": "product_line",
+            "description": "dbt desc",
+            "expression": None,
+            "extra": "{}",
+            "filterable": False,
+            "groupby": True,
+            "id": 1,
+            "is_active": True,
+            "is_dttm": False,
+            "python_date_format": None,
+            "type": None,
+            "uuid": "5b0dc14a-8c1a-4fcb-8791-3a955d8609d3",
+            "verbose_name": None,
+        },
+        {
+            "advanced_data_type": None,
+            "column_name": "id",
+            "description": "Primary key",
+            "expression": None,
+            "extra": "{}",
+            "filterable": False,
+            "groupby": False,
+            "id": 2,
+            "is_dttm": False,
+            "python_date_format": None,
+            "type": "INTEGER",
+            "uuid": "a2952680-2671-4a97-b608-3483cf7f11d2",
+            "verbose_name": "id",
+        },
+    ]
+
+    result = compute_columns_metadata(
+        model_columns,
+        dataset_columns,
+        True,
+        False,
+        column_defaults=default_column_config,
+    )
+    assert result == expected
+
+    result = compute_columns_metadata(
+        model_columns,
+        dataset_columns,
+        False,
+        True,
+        column_defaults=default_column_config,
+    )
+    assert result == expected
+
+
 def test_compute_dataset_metadata_with_dbt_metadata() -> None:
     """
     Test the ``compute_dataset_metadata`` helper with metadata from dbt.