Load Dataset from Dynamically generated Case Class

What is Needed:

number of tables in source database are changing rapidly and thus I don't want to edit case classes so I dynamically generate them through SCALA code and put in package. But now not able to read it dynamically. If this works than I would parse "com.example.datasources.fileSystemSource.schema.{}" as object schema members in loop

What has already been Done:

I have some case classes dynamically generated from schema of database tables as below:

object schema{
case class Users(name: String,
                 favorite_color: String,
                 favorite_numbers: Array[Int])

case class UserData(registration_dttm: Timestamp,
                    id: Int,
                    first_name: String,
                    last_name: String,
                    email: String,
                    gender: String,
                    ip_address: String,
                    cc: String,
                    country: String,
                    birthdate: String,
                    salary: Double,
                    title: String,
                    comments: String)
}

Then i have used them as dynamic type to read in Load[T] function in my Loader.scala as below:

import org.apache.spark.sql.{Dataset, Encoder, SparkSession}

class Load[T <: Product: Encoder](val tableName: String,
                                       val inputPath: String,
                                       val spark: SparkSession,
                                       val saveMode: String,
                                       val outputPath: String,
                                       val metadata: Boolean)
    extends Loader[T] {

  val fileSystemSourceInstance: FileSystem[T] =
    new FileSystem[T](inputPath, spark, saveMode, tableName)

  override def Load: Dataset[T] =
    fileSystemSourceInstance.provideData(metadata, outputPath).as[T]

}

Now, by using reflect.api I am able to get TypeTag for my case classes.

def stringToTypeTag[A](name: String): TypeTag[A] = {
    val c = Class.forName(name)
    val mirror = runtimeMirror(c.getClassLoader)
    val sym = mirror.staticClass(name)
    val tpe = sym.selfType
    TypeTag(mirror, new api.TypeCreator {
      def apply[U <: api.Universe with Singleton](m: api.Mirror[U]) =

        if (m eq mirror) tpe.asInstanceOf[U # Type]
        else throw new IllegalArgumentException(s"Type tag defined in $mirror cannot be migrated to other mirrors.")
    })
  }

So if i print now my case class type tag I got:

val typetagDynamic = stringToTypeTag("com.example.datasources.fileSystemSource.schema.Users")
println(typetags)
TypeTag[com.example.datasources.fileSystemSource.schema.Users]

Problem:

Need to read these TypeTag or Dynamically generated case classes, to encode my datasets as below:

new Load[typetagDynamic](tableName,inputPath,spark,
saveMode,
outputPath + tableName,
metadata)(Encoders.product[typetagDynamic]).Load 

This is giving me error : Cannot resolve symbol typetagDynamic

if used like this:

new Load[typetagDynamic.type](tableName,inputPath,spark,
saveMode,
outputPath + tableName,
metadata)(Encoders.product[typetagDynamic.type]).Load 

This is giving me error : type arguments [T] do not conform to method product's type parameter bounds [T <: Product]