feat: Playtomic pricing/occupancy pipeline + email i18n + audience restructure

Three workstreams:

1. Playtomic full data extraction & transform pipeline:
   - Expand venue bounding boxes from 4 to 23 regions (global coverage)
   - New staging models for court resources, opening hours, and slot-level
     availability with real prices from the Playtomic API
   - Foundation fact tables for venue capacity and daily occupancy/revenue
   - City-level pricing benchmarks replacing hardcoded country estimates
   - Planner defaults now use 3-tier cascade: city data → country → fallback

2. Transactional email i18n:
   - _t() helper in worker.py with ~70 translation keys (EN + DE)
   - All 8 email handlers translated, lang passed in task payloads

3. Resend audiences restructured to 3 named audiences (free plan limit)

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

transform/sqlmesh_padelnomics/models/foundation/dim_cities.sql

@@ -40,6 +40,12 @@ eurostat_labels AS (
     -- Derive a slug-friendly city name from the code as fallback
     LOWER(REPLACE(city_code, country_code, ''))  AS city_slug_raw
   FROM eurostat_cities
+),
+-- Country-level median income (latest year per country)
+country_income AS (
+  SELECT country_code, median_income_pps, ref_year AS income_year
+  FROM staging.stg_income
+  QUALIFY ROW_NUMBER() OVER (PARTITION BY country_code ORDER BY ref_year DESC) = 1
 )
 SELECT
   ec.city_code,
@@ -52,8 +58,12 @@ SELECT
   COALESCE(vc.centroid_lon, 0::DOUBLE)           AS lon,
   ec.population,
   ec.ref_year                                    AS population_year,
-  COALESCE(vc.venue_count, 0)                    AS padel_venue_count
+  COALESCE(vc.venue_count, 0)                    AS padel_venue_count,
+  ci.median_income_pps,
+  ci.income_year
 FROM eurostat_cities ec
 LEFT JOIN venue_counts vc
   ON  ec.country_code = vc.country_code
   AND LOWER(TRIM(vc.city)) LIKE '%' || LOWER(LEFT(ec.city_code, 2)) || '%'
+LEFT JOIN country_income ci
+  ON ec.country_code = ci.country_code