Hello @galzamo how are you?
You can check on the SparkUI for long running stages that might give you a clue where it's spending the most time on each task. Somethings can be the reason:
1. Increase of data and partitions on your source data
2. Cluster concurrency (if you're using a shared cluster with other users)
3. Network and connection issues when connecting to external data sources
If you can share more of your job and the spark logs, we can help you to check.
Best,
Alessandro