The main way we scale data consumption from a Kafka topic is by adding more consumers to the consumer group. It is a common operation for Kafka consumers to do high-latency operations such as writing to databases or a time-consuming computation.
If you know that you will need many consumers to parallelize the processing, you can plan accordingly with the number of partitions to parallel the consumer works.
It’s also important not to have more consumers in a group than you have partitions. The extra consumers will just sit idle, since all the partitions are taken.