perf(dbt): materialize stg_ees_ks2 and stg_ees_ks4 as tables

KS2 attainment has 1.2M rows in long format. As a view, the pivot was
re-executed inline for every downstream model (intermediate → fact),
causing fact_ks2_performance CREATE TABLE to run for 18+ minutes.

Materializing as tables means the pivot runs once during staging, and
downstream models read from a pre-computed ~16k-row result.

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

pipeline/transform/models/staging/stg_ees_ks2.sql

@@ -1,3 +1,5 @@
+{{ config(materialized='table') }}
+
 -- Staging model: KS2 attainment + information
 -- Pivots long-format attainment data (one row per subject × breakdown) into
 -- wide format (one row per school per year) and joins context from info table.

pipeline/transform/models/staging/stg_ees_ks4.sql

@@ -1,3 +1,5 @@
+{{ config(materialized='table') }}
+
 -- Staging model: KS4 attainment data from EES
 -- KS4 performance data is long-format with breakdown dimensions (breakdown_topic,
 -- breakdown, sex). Unlike KS2 which has a subject dimension, KS4 metrics are