diff --git a/pandera/backends/pyspark/builtin_checks.py b/pandera/backends/pyspark/builtin_checks.py
index 4d30eb6f3..514f475c1 100644
--- a/pandera/backends/pyspark/builtin_checks.py
+++ b/pandera/backends/pyspark/builtin_checks.py
@@ -1,9 +1,10 @@
 """PySpark implementation of built-in checks"""
 
-from typing import Any, Iterable, TypeVar
+import re
+from typing import Any, Iterable, Optional, TypeVar
 
 import pyspark.sql.types as pst
-from pyspark.sql.functions import col
+from pyspark.sql.functions import col, length, lit
 
 import pandera.strategies as st
 from pandera.api.extensions import register_builtin_check
@@ -328,3 +329,28 @@ def str_endswith(data: PysparkDataframeColumnObject, string: str) -> bool:
     """
     cond = col(data.column_name).endswith(string)
     return data.dataframe.filter(~cond).limit(1).count() == 0
+
+
+@register_builtin_check(
+    error="str_length({min_value}, {max_value})",
+)
+@register_input_datatypes(acceptable_datatypes=convert_to_list(STRING_TYPE))
+def str_length(
+    data: PysparkDataframeColumnObject,
+    min_value: Optional[int] = None,
+    max_value: Optional[int] = None,
+) -> bool:
+    """Ensure that the length of strings in a column is within a specified range."""
+    if min_value is None and max_value is None:
+        raise ValueError(
+            "Must provide at least one of 'min_value' and 'max_value'"
+        )
+
+    str_len = length(col(data.column_name))
+    cond = lit(True)
+    if min_value is not None:
+        cond = cond & (str_len >= min_value)
+    if max_value is not None:
+        cond = cond & (str_len <= max_value)
+
+    return data.dataframe.filter(~cond).limit(1).count() == 0