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>

backend/models.py

@@ -215,3 +215,25 @@ class FactFinance(Base):
     teacher_cost_pct = Column(Float)
     support_staff_cost_pct = Column(Float)
     premises_cost_pct = Column(Float)
+
+
+class Ks2NationalAverage(Base):
+    """Official DfE KS2 national headline averages — one row per academic year."""
+    __tablename__ = "fact_ks2_national_averages"
+    __table_args__ = MARTS
+
+    year = Column(Integer, primary_key=True)
+    rwm_expected_pct = Column(Float)
+    rwm_high_pct = Column(Float)
+    reading_expected_pct = Column(Float)
+    reading_high_pct = Column(Float)
+    reading_avg_score = Column(Float)
+    writing_expected_pct = Column(Float)
+    writing_gd_pct = Column(Float)
+    maths_expected_pct = Column(Float)
+    maths_high_pct = Column(Float)
+    maths_avg_score = Column(Float)
+    gps_expected_pct = Column(Float)
+    gps_high_pct = Column(Float)
+    gps_avg_score = Column(Float)
+    science_expected_pct = Column(Float)