spark-submit does not find class (while class is being contained in jar)

I am building a very simple HelloWorld Spark job, in Java with Gradle:

package com.example;

public class HelloWorld {
    public static void main(String[] args) {
        System.out.println("Hello World!");
    }
}

My gradle config is very straightforward:

def sparkVersion = "2.4.6"
def hadoopVersion = "2.7.3"

dependencies {
    compile "org.apache.spark:spark-core_2.11:$sparkVersion"
    compile "org.apache.spark:spark-sql_2.11:$sparkVersion"
    compile 'org.slf4j:slf4j-simple:1.7.9'
    compile "org.apache.hadoop:hadoop-aws:$hadoopVersion"
    compile "org.apache.hadoop:hadoop-common:$hadoopVersion"
    testCompile group: 'junit', name: 'junit', version: '4.12'
}

I also made sure I build a far jar to include all the dependencies, like SBT assembly is doing in Scala:

jar {
    zip64 = true
    from {
        configurations.runtimeClasspath.collect { it.isDirectory() ? it : zipTree(it) }
    }
}

The build works well and my class appears in the jar:

jar tvf build/libs/output.jar | grep -i hello
com/example/HelloWorld.class

However, when running spark-submit job:

 spark-submit --class 'com.example.HelloWorld' --master=local build/libs/output.jar

All I am getting is debug logs:

20/09/21 13:07:46 WARN Utils: Your hostname, example.local resolves to a loopback address: 127.0.0.1; using 192.168.43.208 instead (on interface en0)
20/09/21 13:07:46 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
20/09/21 13:07:46 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
log4j:WARN No appenders could be found for logger (org.apache.spark.deploy.SparkSubmit$$anon$2).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.

My local spark is rightfully reporting Scala 2.11 and Spark 2.4.6 built for Hadoop 2.7.3.
I also tested with a more complexe Spark job but the output logs are the same.

The code is however running well in IntelliJ Idea (with option Include dependencies with "Provided" scope ticked).

Am I missing something? Thank you very much

The problem could have come from zip64 = true or from the fat jar generation (although the shadowJar plugin did not fix this either).

I decided to go with Maven instead and use the maven-assembly-plugin for the fat jar generation, the maven-compiler-plugin to only include certain files related to the Spark job I want to build and finally maven-jar-plugin to avoid building a jar containing all the spark jobs (1 job per jar).