diff --git a/server-rs/src/data/property.rs b/server-rs/src/data/property.rs
index d60564f..25f4601 100644
--- a/server-rs/src/data/property.rs
+++ b/server-rs/src/data/property.rs
@@ -656,7 +656,7 @@ impl PropertyData {
 
         tracing::info!("Extracting numeric feature columns");
         let numeric_col_major: Vec<Vec<f32>> = numeric_names
-            .iter()
+            .par_iter()
             .map(|name| {
                 let column = df
                     .column(name)
@@ -733,12 +733,11 @@ impl PropertyData {
 
         tracing::info!("Building enum features");
         // enum_col_major: Vec<(values_list, encoded_as_f32)>
-        let mut enum_col_major: Vec<(Vec<String>, Vec<f32>)> = Vec::new();
-        for &name in &enum_names {
-            if let Ok(column_data) = df.column(name) {
-                let string_column = column_data
-                    .str()
-                    .with_context(|| format!("Enum column '{name}' is not a string column"))?;
+        let enum_col_major: Vec<(Vec<String>, Vec<f32>)> = enum_names
+            .par_iter()
+            .filter_map(|&name| {
+                let column_data = df.column(name).ok()?;
+                let string_column = column_data.str().ok()?;
                 let unique_set: std::collections::HashSet<String> = string_column
                     .into_iter()
                     .filter_map(|value| {
@@ -795,9 +794,9 @@ impl PropertyData {
                     .collect();
 
                 tracing::debug!(column = %name, unique_values = unique.len(), "Enum feature encoded as f32");
-                enum_col_major.push((unique, encoded));
-            }
-        }
+                Some((unique, encoded))
+            })
+            .collect();
 
         // Extract is_approx_build_date: 0.0 = exact, anything else (1.0/NaN) = approximate
         let is_approx_build_date_raw: Vec<bool> = if has_approx_col {
@@ -920,7 +919,7 @@ impl PropertyData {
         let grid_cols = ((max_lon_val - min_lon_val) / grid_cell_size).ceil() as u64 + 1;
 
         let mut perm: Vec<u32> = (0..row_count as u32).collect();
-        perm.sort_unstable_by_key(|&perm_index| {
+        perm.par_sort_unstable_by_key(|&perm_index| {
             let grid_row = ((lat[perm_index as usize] - min_lat_val) / grid_cell_size) as u64;
             let grid_col = ((lon[perm_index as usize] - min_lon_val) / grid_cell_size) as u64;
             grid_row * grid_cols + grid_col
@@ -1036,18 +1035,20 @@ impl PropertyData {
         // Combines numeric and enum features into a single feature_data array.
         tracing::info!("Transposing to row-major layout (spatially sorted)");
         let mut feature_data = vec![f32::NAN; row_count * num_features];
-        for (new_row, &old_row) in perm.iter().enumerate() {
-            let old_index = old_row as usize;
-            let dst_base = new_row * num_features;
-            // Numeric features
-            for (feat_idx, col_vec) in numeric_col_major.iter().enumerate() {
-                feature_data[dst_base + feat_idx] = col_vec[old_index];
-            }
-            // Enum features (stored as f32 indices)
-            for (enum_idx, (_, encoded)) in enum_col_major.iter().enumerate() {
-                feature_data[dst_base + num_numeric + enum_idx] = encoded[old_index];
-            }
-        }
+        feature_data
+            .par_chunks_mut(num_features)
+            .enumerate()
+            .for_each(|(new_row, row_slice)| {
+                let old_index = perm[new_row] as usize;
+                // Numeric features
+                for (feat_idx, col_vec) in numeric_col_major.iter().enumerate() {
+                    row_slice[feat_idx] = col_vec[old_index];
+                }
+                // Enum features (stored as f32 indices)
+                for (enum_idx, (_, encoded)) in enum_col_major.iter().enumerate() {
+                    row_slice[num_numeric + enum_idx] = encoded[old_index];
+                }
+            });
 
         tracing::info!("Data loading complete");