fix(pipeline): invoke dbt via python module to avoid Fusion shadowing

The standalone dbt Fusion binary (dbt-core 2.x) on PATH shadows the
pip-installed classic dbt-postgres ~=1.10 and rejects the Postgres
adapter (dbt1005), breaking every DAG's dbt_build task. Invoke dbt via
`python -m dbt.cli.main` in the DAGs and the Dockerfile dbt deps step so
the classic Postgres-capable engine is always used regardless of PATH.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

pipeline/Dockerfile

@@ -32,8 +32,9 @@ COPY dags/ dags/
 # Initialize Meltano project (generates catalog, installs target-postgres)
 RUN meltano install
 
-# dbt deps
+# dbt deps — invoke via the Python module so the classic dbt-postgres engine
-RUN cd transform && dbt deps --profiles-dir . 2>/dev/null || true
+# is used, not a standalone dbt Fusion binary that may shadow it on PATH.
+RUN cd transform && python -m dbt.cli.main deps --profiles-dir . 2>/dev/null || true
 
 ENV AIRFLOW_HOME=/opt/airflow
 ENV AIRFLOW__CORE__DAGS_FOLDER=/opt/pipeline/dags

pipeline/dags/school_data_pipeline.py

@@ -24,7 +24,11 @@ except ImportError:
 
 PIPELINE_DIR = "/opt/pipeline"
 MELTANO_BIN = "meltano"
-DBT_BIN = "dbt"
+# Invoke dbt via the Python module rather than a bare `dbt` on PATH. The
+# standalone dbt Fusion binary (dbt-core 2.x) shadows the pip-installed
+# classic engine on some images and rejects the Postgres adapter
+# (dbt1005). The module form always resolves to dbt-postgres ~=1.10.
+DBT_BIN = "python -m dbt.cli.main"
 
 default_args = {
     "owner": "school-compare",