Ways to write fast millions of rows inside a new delta table

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Hello everyone,
I am facing an issue with writing 100–500 million rows (partitioned by a column) into a newly created Delta table. I have set up a cluster with 256 GB of memory and 64 cores. However, the following code takes a considerable amount of time even when writing around 70 million rows:

            df.repartition(num_partitions*4, partition_col).write \
                .format("delta") \
                .mode("overwrite") \
                .partitionBy(partition_col) \
                .option("mergeSchema", "true") \
                .option("optimizeBucket", "true") \
                .option("maxRecordsPerFile", "1000000") \
                .option("autoOptimize.optimizeWrite", "true") \
                .option("autoOptimize.autoCompact", "true") \
                .option("autoOptimize.autoRepartition", "true") \
                .saveAsTable(f"{bronze_layer}.{table_name}")

What Do i need to adjust to speed up this written step?