Moving from your existing infrastructure to a new infrastructure incurs a cost in both design and implementation. There is also a cost in training existing people on the new infra.

Without much info to go as to how the infrastructure is complex, the first thing I would suggest is to get rid of operations overhead by going with a hosted service. AWS EMR, Databricks, Qubole, etc. offer a service with S3+Hive+Spark.

The reason for using the tools might not just be volume. It could also be due to vicissitude (large number of different data sources using spark for pre processing), or scaling, or something else. Try to understand why the existing solution is used before planning a migration.

If you are determined to go with a new pipeline, build a prototype for a small subset of data science tasks you have and carefully evaluate the pro and cons vs the existing approach for that subset.