diff --git a/changelog_entry.yaml b/changelog_entry.yaml
index e69de29bb..d6f755478 100644
--- a/changelog_entry.yaml
+++ b/changelog_entry.yaml
@@ -0,0 +1,4 @@
+- bump: minor
+  changes:
+    added:
+      - Add pension_contributions_via_salary_sacrifice variable from FRS SPNAMT field
diff --git a/policyengine_uk_data/datasets/frs.py b/policyengine_uk_data/datasets/frs.py
index 8dd8789c5..56b51042c 100644
--- a/policyengine_uk_data/datasets/frs.py
+++ b/policyengine_uk_data/datasets/frs.py
@@ -631,6 +631,20 @@ def determine_education_level(fted_val, typeed2_val, age_val):
     pe_person["employer_pension_contributions"] = (
         pe_person["employee_pension_contributions"] * 3
     )  # Rough estimate based on aggregates.
+    # Salary sacrifice pension contributions from FRS Job table (SPNAMT field)
+    # SPNAMT represents employer pension contributions made via salary sacrifice
+    # arrangements where employees forego salary in exchange for increased pension
+    # contributions. This is separate from regular employee pension contributions
+    # (deduc1) and provides tax advantages for both employer and employee.
+    # Uses same pattern as employee_pension_contributions (deduc1) without outlier
+    # clipping, as job-level data is generally cleaner than pension provider data.
+    # Source: https://datacatalogue.ukdataservice.ac.uk/datasets/dataset/630d4a8d-ba6a-82b3-f33d-c713c66efcb3
+    # Note: Values are annualized from weekly amounts reported in the survey.
+    pe_person["pension_contributions_via_salary_sacrifice"] = np.maximum(
+        0,
+        sum_to_entity(job.spnamt.fillna(0), job.person_id, person.person_id)
+        * WEEKS_IN_YEAR,
+    )
 
     pe_household["housing_service_charges"] = (
         pd.DataFrame(
diff --git a/policyengine_uk_data/storage/uprating_factors.csv b/policyengine_uk_data/storage/uprating_factors.csv
index 62ab4dacb..5a7e54df4 100644
--- a/policyengine_uk_data/storage/uprating_factors.csv
+++ b/policyengine_uk_data/storage/uprating_factors.csv
@@ -21,6 +21,7 @@ domestic_energy_consumption,1.0,1.04,1.144,1.209,1.237,1.277,1.301,1.327,1.353,1
 education_consumption,1.0,1.04,1.144,1.209,1.237,1.277,1.301,1.327,1.353,1.38,1.38,1.38,1.38,1.38,1.38
 employee_pension_contributions,1.0,1.059,1.127,1.205,1.261,1.308,1.337,1.365,1.396,1.431,1.431,1.431,1.431,1.431,1.431
 employer_pension_contributions,1.0,1.059,1.127,1.205,1.261,1.308,1.337,1.365,1.396,1.431,1.431,1.431,1.431,1.431,1.431
+pension_contributions_via_salary_sacrifice,1.0,1.059,1.127,1.205,1.261,1.308,1.337,1.365,1.396,1.431,1.431,1.431,1.431,1.431,1.431
 employment_income,1.0,1.059,1.127,1.205,1.261,1.308,1.337,1.365,1.396,1.431,1.431,1.431,1.431,1.431,1.431
 employment_income_before_lsr,1.0,1.059,1.127,1.205,1.261,1.308,1.337,1.365,1.396,1.431,1.431,1.431,1.431,1.431,1.431
 esa_contrib_reported,1.0,1.04,1.144,1.209,1.237,1.277,1.301,1.327,1.353,1.38,1.38,1.38,1.38,1.38,1.38
diff --git a/policyengine_uk_data/storage/uprating_growth_factors.csv b/policyengine_uk_data/storage/uprating_growth_factors.csv
index eb1bcca2b..eb8b7fb6d 100644
--- a/policyengine_uk_data/storage/uprating_growth_factors.csv
+++ b/policyengine_uk_data/storage/uprating_growth_factors.csv
@@ -21,6 +21,7 @@ domestic_energy_consumption,0,0.04,0.1,0.057,0.023,0.032,0.019,0.02,0.02,0.02,0.
 education_consumption,0,0.04,0.1,0.057,0.023,0.032,0.019,0.02,0.02,0.02,0.0,0.0,0.0,0.0,0.0
 employee_pension_contributions,0,0.059,0.064,0.069,0.046,0.037,0.022,0.021,0.023,0.025,0.0,0.0,0.0,0.0,0.0
 employer_pension_contributions,0,0.059,0.064,0.069,0.046,0.037,0.022,0.021,0.023,0.025,0.0,0.0,0.0,0.0,0.0
+pension_contributions_via_salary_sacrifice,0,0.059,0.064,0.069,0.046,0.037,0.022,0.021,0.023,0.025,0.0,0.0,0.0,0.0,0.0
 employment_income,0,0.059,0.064,0.069,0.046,0.037,0.022,0.021,0.023,0.025,0.0,0.0,0.0,0.0,0.0
 employment_income_before_lsr,0,0.059,0.064,0.069,0.046,0.037,0.022,0.021,0.023,0.025,0.0,0.0,0.0,0.0,0.0
 esa_contrib_reported,0,0.04,0.1,0.057,0.023,0.032,0.019,0.02,0.02,0.02,0.0,0.0,0.0,0.0,0.0
diff --git a/policyengine_uk_data/tests/test_pension_contributions_via_salary_sacrifice.py b/policyengine_uk_data/tests/test_pension_contributions_via_salary_sacrifice.py
new file mode 100644
index 000000000..57c5edf89
--- /dev/null
+++ b/policyengine_uk_data/tests/test_pension_contributions_via_salary_sacrifice.py
@@ -0,0 +1,24 @@
+def test_pension_contributions_via_salary_sacrifice(baseline):
+    """Test that pension_contributions_via_salary_sacrifice loads and has reasonable values."""
+    values = baseline.calculate(
+        "pension_contributions_via_salary_sacrifice", period=2025
+    )
+
+    # Basic validation: all values should be non-negative
+    assert (
+        values >= 0
+    ).all(), "Salary sacrifice pension contributions must be non-negative"
+
+    # Should have some non-zero values (not everyone uses salary sacrifice, but some do)
+    total = values.sum()
+    assert (
+        total > 0
+    ), f"Expected some salary sacrifice contributions, got {total}"
+
+    # Reasonableness check: total should be less than total employment income
+    # This is a very loose check just to catch major issues
+    employment_income = baseline.calculate("employment_income", period=2025)
+    total_employment = employment_income.sum()
+    assert (
+        total < total_employment
+    ), f"Salary sacrifice contributions ({total/1e9:.1f}B) cannot exceed total employment income ({total_employment/1e9:.1f}B)"