feat: ingest official DfE KS2 national averages from EES data catalogue

Replaces computed means from our school dataset with the published DfE
national headline figures for the KS2 chart reference line.

- tap-uk-ees: new EESKs2NationalStream fetches the stable EES data-catalogue
  CSV (one row per year, England national total, AllSchools filter)
- dbt staging: stg_ees_ks2_national normalises columns, casts to float,
  filters to years >= 201617
- dbt mart: fact_ks2_national_averages — one row per year, official figures
- backend/models: Ks2NationalAverage SQLAlchemy model
- backend/app: /api/national-averages queries the mart for KS2 by_year;
  secondary by_year stays computed (no DfE KS4 national dataset yet)
- DAG: extract_ks2_national task added to school_data_annual_ees,
  runs in parallel with the main EES extract

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

pipeline/dags/school_data_pipeline.py

@@ -137,10 +137,15 @@ with DAG(
             task_id="extract_ees",
             bash_command=f"cd {PIPELINE_DIR} && {MELTANO_BIN} run tap-uk-ees target-postgres",
         )
+        # KS2 national headlines run in parallel — small single-CSV download
+        extract_ks2_national = BashOperator(
+            task_id="extract_ks2_national",
+            bash_command=f"cd {PIPELINE_DIR} && {MELTANO_BIN} run tap-uk-ees target-postgres --select ees_ks2_national",
+        )
 
     dbt_build_ees = BashOperator(
         task_id="dbt_build",
-        bash_command=f"cd {PIPELINE_DIR}/transform && {DBT_BIN} build --profiles-dir . --target production --select stg_ees_ks2+ stg_legacy_ks2+ stg_ees_ks4+ stg_ees_census+ stg_ees_admissions+",
+        bash_command=f"cd {PIPELINE_DIR}/transform && {DBT_BIN} build --profiles-dir . --target production --select stg_ees_ks2+ stg_legacy_ks2+ stg_ees_ks4+ stg_ees_census+ stg_ees_admissions+ stg_ees_ks2_national+",
     )
 
     sync_typesense_ees = BashOperator(