Add parallel checker execution with connection pooling

Implements Level 2 parallelization for row_count, schema, and
aggregate checkers, improving performance by 2-3x for tables with
multiple enabled checks.

Changes:
- Add max_workers config option (default: 4)
- Add ConnectionPool module with SQLAlchemy QueuePool
- Add URL encoding for connection strings
- Implement parallel checker execution with ThreadPoolExecutor
- Add fail-fast behavior on checker errors
- Update executor for SQLAlchemy 2.0 compatibility
- Fix engine disposal resource leak
- Cache pooled engines in ConnectionManager
- Add disconnect() cleanup for pooled engines

Performance:
- Sequential: 3 checkers × 100ms = 300ms
- Parallel: 3 checkers ≈ 100ms (2-3x speedup)

Configuration:
  execution:
    max_workers: 4  # Controls parallel checker execution
    continue_on_error: true

config.example.yaml

@@ -195,22 +195,19 @@ logging:
 # Configure execution behavior
 # ============================================================================
 execution:
-  # Parallel execution (future feature)
-  parallel:
-    enabled: false
-    max_workers: 4
+  # Continue execution even if a table check fails
+  continue_on_error: true
+  
+  # Maximum number of parallel workers for checker execution
+  # Higher values = more parallel execution, but more database connections
+  # Recommended: 4 for most scenarios, 8 for high-performance servers
+  # Connection pool size = max_workers + 2
+  max_workers: 4
   
   # Retry settings for transient failures
   retry:
-    enabled: true
-    max_attempts: 3
+    attempts: 3
     delay_seconds: 5
-  
-  # Performance settings
-  performance:
-    batch_size: 1000        # Rows per batch for large queries
-    use_nolock: true        # Use NOLOCK hints (read uncommitted)
-    connection_pooling: true
 
 # ============================================================================
 # FILTERS