diff --git a/src/main/scala/com/github/mrpowers/spark/daria/sql/DataFrameSchemaChecker.scala b/src/main/scala/com/github/mrpowers/spark/daria/sql/DataFrameSchemaChecker.scala
index 4061098..8cdeb4a 100644
--- a/src/main/scala/com/github/mrpowers/spark/daria/sql/DataFrameSchemaChecker.scala
+++ b/src/main/scala/com/github/mrpowers/spark/daria/sql/DataFrameSchemaChecker.scala
@@ -1,13 +1,42 @@
 package com.github.mrpowers.spark.daria.sql
 
 import org.apache.spark.sql.DataFrame
-import org.apache.spark.sql.types.StructType
+import org.apache.spark.sql.types.{StructField, StructType}
+
+import scala.annotation.tailrec
+import scala.util.{Failure, Success, Try}
 
 case class InvalidDataFrameSchemaException(smth: String) extends Exception(smth)
 
 private[sql] class DataFrameSchemaChecker(df: DataFrame, requiredSchema: StructType) {
+  private def diff(required: Seq[StructField], schema: StructType): Seq[StructField] = {
+    required.filterNot(isPresentIn(schema))
+  }
+
+  private def isPresentIn(schema: StructType)(reqField: StructField): Boolean = {
+    Try(schema(reqField.name)) match {
+      case Success(namedField) =>
+        val basicMatch =
+          namedField.name == reqField.name &&
+            (!namedField.nullable || reqField.nullable) &&
+            namedField.metadata == reqField.metadata
+        val contentMatch = reqField.dataType match {
+          case reqSchema: StructType =>
+            namedField.dataType match {
+              case fieldSchema: StructType =>
+                diff(reqSchema, fieldSchema).isEmpty
+              case _ => false
+            }
+          case namedField.dataType => true
+          case _                   => false
+        }
+
+        basicMatch && contentMatch
+      case Failure(_) => false
+    }
+  }
 
-  val missingStructFields = requiredSchema.diff(df.schema)
+  val missingStructFields: Seq[StructField] = diff(requiredSchema, df.schema)
 
   def missingStructFieldsMessage(): String = {
     s"The [${missingStructFields.mkString(", ")}] StructFields are not included in the DataFrame with the following StructFields [${df.schema.toString()}]"
diff --git a/src/test/scala/com/github/mrpowers/spark/daria/sql/DariaValidatorTest.scala b/src/test/scala/com/github/mrpowers/spark/daria/sql/DariaValidatorTest.scala
index b863424..07e8500 100644
--- a/src/test/scala/com/github/mrpowers/spark/daria/sql/DariaValidatorTest.scala
+++ b/src/test/scala/com/github/mrpowers/spark/daria/sql/DariaValidatorTest.scala
@@ -170,6 +170,128 @@ object DariaValidatorTest extends TestSuite with SparkSessionTestWrapper {
 
       }
 
+      "matches schema when fields are out of order" - {
+        val zoo = StructField(
+          "zoo",
+          StringType,
+          true
+        )
+        val zaa = StructField(
+          "zaa",
+          StringType,
+          true
+        )
+        val bar = StructField(
+          "bar",
+          StructType(
+            Seq(
+              zaa,
+              zoo
+            )
+          )
+        )
+        val baz = StructField(
+          "baz",
+          StringType,
+          true
+        )
+        val foo = StructField(
+          "foo",
+          StructType(
+            Seq(
+              baz,
+              bar
+            )
+          ),
+          true
+        )
+        val z = StructField(
+          "z",
+          StringType,
+          true
+        )
+
+        def validateSchemaEquality(s1: StructType, s2: StructType) = {
+          val df = spark
+            .createDataFrame(
+              spark.sparkContext.parallelize(Seq[Row]()),
+              s1
+            )
+
+          df.printSchema()
+          spark
+            .createDataFrame(
+              spark.sparkContext.parallelize(Seq[Row]()),
+              s2
+            )
+            .printSchema()
+
+          DariaValidator.validateSchema(
+            df,
+            s2
+          )
+        }
+
+        // Shallow equality
+        validateSchemaEquality(
+          StructType(
+            Seq(z, foo)
+          ),
+          StructType(
+            Seq(foo, z)
+          )
+        )
+
+        // Second level equality
+        val foo2 = StructField(
+          "foo",
+          StructType(
+            Seq(
+              bar,
+              baz
+            )
+          ),
+          true
+        )
+        validateSchemaEquality(
+          StructType(
+            Seq(z, foo)
+          ),
+          StructType(
+            Seq(z, foo2)
+          )
+        )
+
+        // Third level equality - just to make sure
+        val bar2 = StructField(
+          "bar",
+          StructType(
+            Seq(
+              zoo,
+              zaa
+            )
+          )
+        )
+        val foo3 = StructField(
+          "foo",
+          StructType(
+            Seq(
+              baz,
+              bar2
+            )
+          ),
+          true
+        )
+        validateSchemaEquality(
+          StructType(
+            Seq(z, foo)
+          ),
+          StructType(
+            Seq(z, foo3)
+          )
+        )
+      }
+
     }
 
     'validateAbsenceOfColumns - {
diff --git a/src/test/scala/com/github/mrpowers/spark/daria/sql/DataFrameSchemaCheckerTest.scala b/src/test/scala/com/github/mrpowers/spark/daria/sql/DataFrameSchemaCheckerTest.scala
index b7c6823..a136aee 100644
--- a/src/test/scala/com/github/mrpowers/spark/daria/sql/DataFrameSchemaCheckerTest.scala
+++ b/src/test/scala/com/github/mrpowers/spark/daria/sql/DataFrameSchemaCheckerTest.scala
@@ -363,6 +363,40 @@ object DataFrameSchemaCheckerTest extends TestSuite with SparkSessionTestWrapper
 
       }
 
+      "validates non-null column against a null schema" - {
+        val sourceSchema = List(
+          StructField(
+            "num",
+            IntegerType,
+            false
+          )
+        )
+
+        val sourceDF =
+          spark.createDataFrame(
+            spark.sparkContext.parallelize(Seq[Row]()),
+            StructType(sourceSchema)
+          )
+
+        val requiredSchema =
+          StructType(
+            List(
+              StructField(
+                "num",
+                IntegerType,
+                true
+              )
+            )
+          )
+
+        val c = new DataFrameSchemaChecker(
+          sourceDF,
+          requiredSchema
+        )
+
+        c.validateSchema()
+      }
+
     }
 
   }