diff --git a/pipeline/plugins/extractors/tap-uk-ees/tap_uk_ees/tap.py b/pipeline/plugins/extractors/tap-uk-ees/tap_uk_ees/tap.py
index f9e5756..9f550c2 100644
--- a/pipeline/plugins/extractors/tap-uk-ees/tap_uk_ees/tap.py
+++ b/pipeline/plugins/extractors/tap-uk-ees/tap_uk_ees/tap.py
@@ -50,6 +50,7 @@ class EESDatasetStream(Stream):
     _publication_slug: str = ""
     _target_filename: str = ""  # keyword that appears in the CSV path
     _urn_column: str = "school_urn"  # column name for URN in the CSV
+    _encoding: str = "utf-8"  # CSV file encoding (some DfE files use latin-1)
 
     def get_records(self, context):
         import pandas as pd
@@ -80,7 +81,7 @@ class EESDatasetStream(Stream):
 
         self.logger.info("Reading %s from ZIP", target)
         with zf.open(target) as f:
-            df = pd.read_csv(f, dtype=str, keep_default_na=False)
+            df = pd.read_csv(f, dtype=str, keep_default_na=False, encoding=self._encoding)
 
         # Filter to school-level data if the column exists
         if "geographic_level" in df.columns:
@@ -266,6 +267,7 @@ class EESCensusStream(EESDatasetStream):
     _publication_slug = "school-pupils-and-their-characteristics"
     _target_filename = "spc_school_level_underlying_data"
     _urn_column = "urn"
+    _encoding = "latin-1"
     schema = th.PropertiesList(
         th.Property("time_period", th.StringType, required=True),
         th.Property("school_urn", th.StringType, required=True),
@@ -287,6 +289,7 @@ class EESAdmissionsStream(EESDatasetStream):
     primary_keys = ["school_urn", "time_period"]
     _publication_slug = "primary-and-secondary-school-applications-and-offers"
     _target_filename = "SchoolLevel"
+    _encoding = "latin-1"
     schema = th.PropertiesList(
         th.Property("time_period", th.StringType, required=True),
         th.Property("school_urn", th.StringType, required=True),