diff --git a/ingestion_server/ingestion_server/cleanup.py b/ingestion_server/ingestion_server/cleanup.py
index 6e794f290d7..da092a324ce 100644
--- a/ingestion_server/ingestion_server/cleanup.py
+++ b/ingestion_server/ingestion_server/cleanup.py
@@ -217,7 +217,7 @@ def _clean_data_worker(rows, temp_table, sources_config, all_fields: list[str]):
     write_cur = worker_conn.cursor(cursor_factory=DictCursor)
     log.info(f"Cleaning {len(rows)} rows")
 
-    start_time = time.time()
+    start_time = time.perf_counter()
     cleaned_values = {field: [] for field in all_fields}
     for row in rows:
         source, _id, identifier = row["source"], row["id"], row["identifier"]
@@ -266,7 +266,7 @@ def _clean_data_worker(rows, temp_table, sources_config, all_fields: list[str]):
     worker_conn.commit()
     write_cur.close()
     worker_conn.close()
-    end_time = time.time()
+    end_time = time.perf_counter()
     total_time = end_time - start_time
     log.info(f"Worker finished batch in {total_time}")
     return cleaned_values
@@ -274,7 +274,7 @@ def _clean_data_worker(rows, temp_table, sources_config, all_fields: list[str]):
 
 def save_cleaned_data(result: dict) -> dict[str, int]:
     log.info("Saving cleaned data...")
-    start_time = time.time()
+    start_time = time.perf_counter()
 
     cleanup_counts = {field: len(items) for field, items in result.items()}
     for field, cleaned_items in result.items():
@@ -286,9 +286,9 @@ def save_cleaned_data(result: dict) -> dict[str, int]:
                 csv_writer = csv.writer(f, delimiter="\t")
                 csv_writer.writerows(cleaned_items)
 
-    end_time = time.time()
+    end_time = time.perf_counter()
     total_time = end_time - start_time
-    log.info(f"Finished saving cleaned data in {total_time},\n{cleanup_counts}")
+    log.info(f"Finished saving cleaned data in {total_time:.3f},\n{cleanup_counts}")
     return cleanup_counts
 
 
@@ -303,7 +303,7 @@ def clean_image_data(table):
     # Map each table to the fields that need to be cleaned up. Then, map each
     # field to its cleanup function.
     log.info("Cleaning up data...")
-    start_time = time.time()
+    start_time = time.perf_counter()
     table_config = _cleanup_config["tables"][table]
 
     # Pull data from selected sources only.
@@ -341,7 +341,7 @@ def clean_image_data(table):
 
         while batch:
             # Divide updates into jobs for parallel execution.
-            batch_start_time = time.time()
+            batch_start_time = time.perf_counter()
             temp_table = f"temp_import_{table}"
             job_size = int(len(batch) / num_workers)
             last_end = -1
@@ -371,7 +371,7 @@ def clean_image_data(table):
                 pool.join()
 
             num_cleaned += len(batch)
-            batch_end_time = time.time()
+            batch_end_time = time.perf_counter()
             rate = len(batch) / (batch_end_time - batch_start_time)
             log.info(
                 f"Batch finished, records/s: cleanup_rate={rate}, "
@@ -383,9 +383,9 @@ def clean_image_data(table):
     conn.commit()
     iter_cur.close()
     conn.close()
-    end_time = time.time()
+    end_time = time.perf_counter()
     cleanup_time = end_time - start_time
     log.info(
-        f"Cleaned all records in {cleanup_time} seconds,"
+        f"Cleaned all records in {cleanup_time:.3f} seconds,"
         f"counts: {cleaned_counts_by_field}"
     )