diff --git a/.changes/unreleased/Under the Hood-20220916-125706.yaml b/.changes/unreleased/Under the Hood-20220916-125706.yaml
new file mode 100644
index 000000000..54b82eb55
--- /dev/null
+++ b/.changes/unreleased/Under the Hood-20220916-125706.yaml	
@@ -0,0 +1,7 @@
+kind: Under the Hood
+body: Enable Pandas and Pandas-on-Spark DataFrames for dbt python models
+time: 2022-09-16T12:57:06.846297-06:00
+custom:
+  Author: chamini2 dbeatty10
+  Issue: "468"
+  PR: "469"
diff --git a/dbt/include/spark/macros/materializations/table.sql b/dbt/include/spark/macros/materializations/table.sql
index d39ba0b44..25d70c722 100644
--- a/dbt/include/spark/macros/materializations/table.sql
+++ b/dbt/include/spark/macros/materializations/table.sql
@@ -41,7 +41,40 @@
 # --- Autogenerated dbt materialization code. --- #
 dbt = dbtObj(spark.table)
 df = model(dbt, spark)
-df.write.mode("overwrite").format("delta").saveAsTable("{{ target_relation }}")
+
+import importlib.util
+
+pandas_available = False
+pyspark_available = False
+
+# make sure pandas exists before using it
+if importlib.util.find_spec("pandas"):
+  import pandas
+  pandas_available = True
+
+# make sure pyspark.pandas exists before using it
+if importlib.util.find_spec("pyspark.pandas"):
+  import pyspark.pandas
+  pyspark_available = True
+
+# preferentially convert pandas DataFrames to pandas-on-Spark DataFrames first
+# since they know how to convert pandas DataFrames better than `spark.createDataFrame(df)`
+# and converting from pandas-on-Spark to Spark DataFrame has no overhead
+if pyspark_available and pandas_available and isinstance(df, pandas.core.frame.DataFrame):
+  df = pyspark.pandas.frame.DataFrame(df)
+
+# convert to pyspark.sql.dataframe.DataFrame
+if isinstance(df, pyspark.sql.dataframe.DataFrame):
+  pass  # since it is already a Spark DataFrame
+elif pyspark_available and isinstance(df, pyspark.pandas.frame.DataFrame):
+  df = df.to_spark()
+elif pandas_available and isinstance(df, pandas.core.frame.DataFrame):
+  df = spark.createDataFrame(df)
+else:
+  msg = f"{type(df)} is not a supported type for dbt Python materialization"
+  raise Exception(msg)
+
+df.write.mode("overwrite").format("delta").option("overwriteSchema", "true").saveAsTable("{{ target_relation }}")
 {%- endmacro -%}
 
 {%macro py_script_comment()%}