diff --git a/CHANGELOG.md b/CHANGELOG.md
index 57878f7f4..fd2cf9b1a 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -6,11 +6,10 @@
 
 
 ### Fixes
-
 - Cast `table_owner` to string to avoid errors generating docs ([#158](https://github.com/fishtown-analytics/dbt-spark/pull/158), [#159](https://github.com/fishtown-analytics/dbt-spark/pull/159))
+- Explicitly cast column types when inserting seeds ([#139](https://github.com/fishtown-analytics/dbt-spark/pull/139), [#166](https://github.com/fishtown-analytics/dbt-spark/pull/166))
 
 ### Under the hood
-
 - Parse information returned by `list_relations_without_caching` macro to speed up catalog generation ([#93](https://github.com/fishtown-analytics/dbt-spark/issues/93), [#160](https://github.com/fishtown-analytics/dbt-spark/pull/160))
 - More flexible host passing, https:// can be omitted ([#153](https://github.com/fishtown-analytics/dbt-spark/issues/153))
 
diff --git a/dbt/include/spark/macros/materializations/seed.sql b/dbt/include/spark/macros/materializations/seed.sql
index c857f013b..795f49329 100644
--- a/dbt/include/spark/macros/materializations/seed.sql
+++ b/dbt/include/spark/macros/materializations/seed.sql
@@ -1,6 +1,7 @@
 {% macro spark__load_csv_rows(model, agate_table) %}
     {% set batch_size = 1000 %}
-
+    {% set column_override = model['config'].get('column_types', {}) %}
+    
     {% set statements = [] %}
 
     {% for chunk in agate_table.rows | batch(batch_size) %}
@@ -13,12 +14,10 @@
         {% set sql %}
             insert into {{ this.render() }} values
             {% for row in chunk -%}
-                ({%- for column in agate_table.columns -%}
-                    {%- if 'ISODate' in (column.data_type | string) -%}
-                      cast(%s as timestamp)
-                    {%- else -%}
-                    %s
-                    {%- endif -%}
+                ({%- for col_name in agate_table.column_names -%}
+                    {%- set inferred_type = adapter.convert_type(agate_table, loop.index0) -%}
+                    {%- set type = column_override.get(col_name, inferred_type) -%}
+                      cast(%s as {{type}})
                     {%- if not loop.last%},{%- endif %}
                 {%- endfor -%})
                 {%- if not loop.last%},{%- endif %}
diff --git a/test/custom/seed_column_types/data/payments.csv b/test/custom/seed_column_types/data/payments.csv
new file mode 100644
index 000000000..3f49d788c
--- /dev/null
+++ b/test/custom/seed_column_types/data/payments.csv
@@ -0,0 +1,11 @@
+ID,ORDERID,PAYMENTMETHOD,STATUS,AMOUNT,AMOUNT_USD,CREATED
+1,1,credit_card,success,1000,10.00,2018-01-01
+2,2,credit_card,success,2000,20.00,2018-01-02
+3,3,coupon,success,100,1.00,2018-01-04
+4,4,coupon,success,2500,25.00,2018-01-05
+5,5,bank_transfer,fail,1700,17.00,2018-01-05
+6,5,bank_transfer,success,1700,17.00,2018-01-05
+7,6,credit_card,success,600,6.00,2018-01-07
+8,7,credit_card,success,1600,16.00,2018-01-09
+9,8,credit_card,success,2300,23.00,2018-01-11
+10,9,gift_card,success,2300,23.00,2018-01-12
diff --git a/test/custom/seed_column_types/test_seed_column_types.py b/test/custom/seed_column_types/test_seed_column_types.py
new file mode 100644
index 000000000..e1fc32788
--- /dev/null
+++ b/test/custom/seed_column_types/test_seed_column_types.py
@@ -0,0 +1,36 @@
+from cProfile import run
+from test.custom.base import DBTSparkIntegrationTest, use_profile
+import dbt.exceptions
+
+
+class TestSeedColumnTypeCast(DBTSparkIntegrationTest):
+    @property
+    def schema(self):
+        return "seed_column_types"
+        
+    @property
+    def models(self):
+        return "models"
+
+    @property
+    def project_config(self):
+        return {
+            'seeds': {
+                'quote_columns': False,
+            },
+        }
+
+    # runs on Spark v2.0
+    @use_profile("apache_spark")
+    def test_seed_column_types_apache_spark(self):
+        self.run_dbt(["seed"])
+
+    # runs on Spark v3.0
+    @use_profile("databricks_cluster")
+    def test_seed_column_types_databricks_cluster(self):
+        self.run_dbt(["seed"])
+
+    # runs on Spark v3.0
+    @use_profile("databricks_sql_endpoint")
+    def test_seed_column_types_databricks_sql_endpoint(self):
+        self.run_dbt(["seed"])