diff --git a/imap_processing/hit/l0/constants.py b/imap_processing/hit/l0/constants.py
index 961ff4b84c..2ac855242a 100644
--- a/imap_processing/hit/l0/constants.py
+++ b/imap_processing/hit/l0/constants.py
@@ -100,7 +100,9 @@
     "penfgrates": HITPacking(16, 528, (33,)),  # range 4 foreground rates
     "penbgrates": HITPacking(16, 240, (15,)),  # range 4 background rates
     "ialirtrates": HITPacking(16, 320, (20,)),  # ialirt rates
-    "sectorates": HITPacking(16, 1920, (15, 8)),  # sectored rates
+    "sectorates": HITPacking(
+        16, 1920, (8, 15)
+    ),  # sectored rates (8 zenith angles, 15 azimuth angles)
     "l4fgrates": HITPacking(16, 768, (48,)),  # all range foreground rates
     "l4bgrates": HITPacking(16, 384, (24,)),  # all range foreground rates
 }
diff --git a/imap_processing/hit/l0/decom_hit.py b/imap_processing/hit/l0/decom_hit.py
index bfea20e51a..571702a12d 100644
--- a/imap_processing/hit/l0/decom_hit.py
+++ b/imap_processing/hit/l0/decom_hit.py
@@ -92,8 +92,11 @@ def parse_count_rates(sci_dataset: xr.Dataset) -> None:
         # Get dims for data variables (yaml file not created yet)
         if len(field_meta.shape) > 1:
             if "sectorates" in field:
-                # Reshape data to 15x8 for azimuth and zenith look directions
+                # Reshape data into (num_frames, 8, 15) for zenith and azimuth
+                # look directions
                 parsed_data = np.array(parsed_data).reshape((-1, *field_meta.shape))
+                # Transpose data to (num_frames, 15, 8) for flipped look directions
+                parsed_data = np.transpose(parsed_data, axes=(0, 2, 1))
                 dims = ["epoch", "azimuth", "zenith"]
                 # Add angle values to coordinates
                 sci_dataset.coords["zenith"] = xr.DataArray(
diff --git a/imap_processing/hit/l1a/hit_l1a.py b/imap_processing/hit/l1a/hit_l1a.py
index 9d1d074a64..ed165fd22d 100644
--- a/imap_processing/hit/l1a/hit_l1a.py
+++ b/imap_processing/hit/l1a/hit_l1a.py
@@ -13,7 +13,11 @@
     get_datasets_by_apid,
     process_housekeeping_data,
 )
-from imap_processing.hit.l0.constants import MOD_10_MAPPING
+from imap_processing.hit.l0.constants import (
+    AZIMUTH_ANGLES,
+    MOD_10_MAPPING,
+    ZENITH_ANGLES,
+)
 from imap_processing.hit.l0.decom_hit import decom_hit
 
 logger = logging.getLogger(__name__)
@@ -104,12 +108,16 @@ def subcom_sectorates(sci_dataset: xr.Dataset) -> xr.Dataset:
     hdr_min_count_mod_10 = updated_dataset.hdr_minute_cnt.values % 10
 
     # Reference mod 10 mapping to initialize data structure for species and
-    # energy ranges and add 15x8 arrays with fill values for each science frame.
+    # energy ranges and add arrays with fill values for each science frame.
     num_frames = len(hdr_min_count_mod_10)
     data_by_species_and_energy_range = {
         key: {
             **value,
-            "counts": np.full((num_frames, 15, 8), fill_value=fillval, dtype=np.int64),
+            "counts": np.full(
+                (num_frames, len(AZIMUTH_ANGLES), len(ZENITH_ANGLES)),
+                fill_value=fillval,
+                dtype=np.int64,
+            ),
         }
         for key, value in MOD_10_MAPPING.items()
     }