diff --git a/catalog/dags/database/recreate_popularity_calculation_dag_factory.py b/catalog/dags/database/recreate_popularity_calculation_dag_factory.py
deleted file mode 100644
index 7381b1d28aa..00000000000
--- a/catalog/dags/database/recreate_popularity_calculation_dag_factory.py
+++ /dev/null
@@ -1,138 +0,0 @@
-"""
-This file generates Apache Airflow DAGs that, for the given media type,
-completely wipe out the PostgreSQL relations and functions involved in
-calculating our standardized popularity metric. It then recreates relations
-and functions to make the calculation, and performs an initial calculation.
-The results are available in the materialized view for that media type.
-
-These DAGs are not on a schedule, and should only be run manually when new
-SQL code is deployed for the calculation.
-"""
-from airflow import DAG
-from airflow.operators.python import PythonOperator
-
-from common.constants import DAG_DEFAULT_ARGS, POSTGRES_CONN_ID
-from common.popularity import sql
-from data_refresh.data_refresh_types import DATA_REFRESH_CONFIGS, DataRefresh
-
-
-def create_recreate_popularity_calculation_dag(data_refresh: DataRefresh):
-    media_type = data_refresh.media_type
-    default_args = {
-        **DAG_DEFAULT_ARGS,
-        **data_refresh.default_args,
-    }
-
-    dag = DAG(
-        dag_id=f"recreate_{media_type}_popularity_calculation",
-        default_args=default_args,
-        max_active_runs=1,
-        schedule=None,
-        catchup=False,
-        doc_md=__doc__,
-        tags=["database", "data_refresh"],
-    )
-    with dag:
-        drop_relations = PythonOperator(
-            task_id="drop_popularity_relations",
-            python_callable=sql.drop_media_popularity_relations,
-            op_kwargs={
-                "postgres_conn_id": POSTGRES_CONN_ID,
-                "media_type": media_type,
-            },
-            doc="Drop the existing popularity views and tables.",
-        )
-
-        drop_functions = PythonOperator(
-            task_id="drop_popularity_functions",
-            python_callable=sql.drop_media_popularity_functions,
-            op_kwargs={
-                "postgres_conn_id": POSTGRES_CONN_ID,
-                "media_type": media_type,
-            },
-            doc="Drop the existing popularity functions.",
-        )
-
-        create_metrics_table = PythonOperator(
-            task_id="create_popularity_metrics_table",
-            python_callable=sql.create_media_popularity_metrics,
-            op_kwargs={
-                "postgres_conn_id": POSTGRES_CONN_ID,
-                "media_type": media_type,
-            },
-            doc=(
-                "Create the popularity metrics table, which stores popularity "
-                "metrics and target percentiles per provider."
-            ),
-        )
-
-        update_metrics_table = PythonOperator(
-            task_id="update_popularity_metrics_table",
-            python_callable=sql.update_media_popularity_metrics,
-            op_kwargs={
-                "postgres_conn_id": POSTGRES_CONN_ID,
-                "media_type": media_type,
-            },
-            doc="Update the popularity metrics table with values for each provider.",
-        )
-
-        create_percentile_function = PythonOperator(
-            task_id="create_popularity_percentile_function",
-            python_callable=sql.create_media_popularity_percentile_function,
-            op_kwargs={
-                "postgres_conn_id": POSTGRES_CONN_ID,
-                "media_type": media_type,
-            },
-            doc=(
-                "Create the function for calculating popularity percentile values, "
-                "used for calculating the popularity constants for each provider."
-            ),
-        )
-
-        create_popularity_function = PythonOperator(
-            task_id="create_standardized_popularity_function",
-            python_callable=sql.create_standardized_media_popularity_function,
-            op_kwargs={
-                "postgres_conn_id": POSTGRES_CONN_ID,
-                "media_type": media_type,
-            },
-            doc=(
-                "Create the function that calculates popularity data for a given "
-                "record, standardizing across providers with the generated popularity "
-                "constants."
-            ),
-        )
-
-        create_matview = PythonOperator(
-            task_id="create_materialized_popularity_view",
-            python_callable=sql.create_media_view,
-            op_kwargs={
-                "postgres_conn_id": POSTGRES_CONN_ID,
-                "media_type": media_type,
-            },
-            execution_timeout=data_refresh.create_materialized_view_timeout,
-            doc=(
-                "Create the materialized view containing standardized popularity data "
-                "for all records."
-            ),
-        )
-
-        (
-            [drop_relations, drop_functions]
-            >> create_metrics_table
-            >> [update_metrics_table, create_percentile_function]
-            >> create_popularity_function
-            >> create_matview
-        )
-
-    return dag
-
-
-# Generate a recreate_popularity_calculation DAG for each DATA_REFRESH_CONFIG.
-for data_refresh in DATA_REFRESH_CONFIGS:
-    recreate_popularity_calculation_dag = create_recreate_popularity_calculation_dag(
-        data_refresh
-    )
-    globals()[
-        recreate_popularity_calculation_dag.dag_id
-    ] = recreate_popularity_calculation_dag