diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
index ff686d024f11..e4f7d77ac731 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRowConverter.scala
@@ -33,8 +33,9 @@ import org.apache.parquet.schema.PrimitiveType.PrimitiveTypeName.{BINARY, DOUBLE
 import org.apache.spark.internal.Logging
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.catalyst.expressions._
-import org.apache.spark.sql.catalyst.util.{ArrayBasedMapData, DateTimeUtils, GenericArrayData}
+import org.apache.spark.sql.catalyst.util.{ArrayBasedMapData, CaseInsensitiveMap, DateTimeUtils, GenericArrayData}
 import org.apache.spark.sql.catalyst.util.DateTimeUtils.SQLTimestamp
+import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.types._
 import org.apache.spark.unsafe.types.UTF8String
 
@@ -178,8 +179,15 @@ private[parquet] class ParquetRowConverter(
 
   // Converters for each field.
   private[this] val fieldConverters: Array[Converter with HasParentContainerUpdater] = {
+    // (SPARK-31116) Use case insensitive map if spark.sql.caseSensitive is false
+    // to prevent throwing IllegalArgumentException when searching catalyst type's field index
+    val catalystFieldNameToIndex = if (SQLConf.get.caseSensitiveAnalysis) {
+      catalystType.fieldNames.zipWithIndex.toMap
+    } else {
+      CaseInsensitiveMap(catalystType.fieldNames.zipWithIndex.toMap)
+    }
     parquetType.getFields.asScala.map { parquetField =>
-      val fieldIndex = catalystType.fieldIndex(parquetField.getName)
+      val fieldIndex = catalystFieldNameToIndex(parquetField.getName)
       val catalystField = catalystType(fieldIndex)
       // Converted field value should be set to the `fieldIndex`-th cell of `currentRow`
       newConverter(parquetField, catalystField.dataType, new RowUpdater(currentRow, fieldIndex))
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala
index c87095812848..cb410b4f0d7d 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/FileBasedDataSourceSuite.scala
@@ -842,6 +842,46 @@ class FileBasedDataSourceSuite extends QueryTest
       }
     }
   }
+
+  test("SPARK-31116: Select nested schema with case insensitive mode") {
+    // This test case failed at only Parquet. ORC is added for test coverage parity.
+    Seq("orc", "parquet").foreach { format =>
+      Seq("true", "false").foreach { nestedSchemaPruningEnabled =>
+        withSQLConf(
+          SQLConf.CASE_SENSITIVE.key -> "false",
+          SQLConf.NESTED_SCHEMA_PRUNING_ENABLED.key -> nestedSchemaPruningEnabled) {
+          withTempPath { dir =>
+            val path = dir.getCanonicalPath
+
+            // Prepare values for testing nested parquet data
+            spark
+              .range(1L)
+              .selectExpr("NAMED_STRUCT('lowercase', id, 'camelCase', id + 1) AS StructColumn")
+              .write
+              .format(format)
+              .save(path)
+
+            val exactSchema = "StructColumn struct<lowercase: LONG, camelCase: LONG>"
+
+            checkAnswer(spark.read.schema(exactSchema).format(format).load(path), Row(Row(0, 1)))
+
+            // In case insensitive manner, parquet's column cases are ignored
+            val innerColumnCaseInsensitiveSchema =
+              "StructColumn struct<Lowercase: LONG, camelcase: LONG>"
+            checkAnswer(
+              spark.read.schema(innerColumnCaseInsensitiveSchema).format(format).load(path),
+              Row(Row(0, 1)))
+
+            val rootColumnCaseInsensitiveSchema =
+              "structColumn struct<lowercase: LONG, camelCase: LONG>"
+            checkAnswer(
+              spark.read.schema(rootColumnCaseInsensitiveSchema).format(format).load(path),
+              Row(Row(0, 1)))
+          }
+        }
+      }
+    }
+  }
 }
 
 object TestingUDT {