Recommendation for storage of series of time series
I can suggest Akumuli.
It's a time-series database that supports compression and high-throughput data ingestion. With 25KHz measurement frequency and 20 engines, you will need to write 500K data points per second in the worst case. Akumuli can handle an order of magnitude larger throughput (largest throughput ever recorded is around 16M data points per second).

Also, because of compression, the database needs only around 3-9 bytes per data point. Each data point is a timestamp with nanosecond precision + 64-bit floating point value. There is an automatic data retention that deletes old data only if there is not enough disk space to store the new data.

You can store data from each engine in the same time-series or you can create new time-series per burst.

The real time-series database can be a big win because you won't need to use all these fancy tricks. There is a downsides of cause. E.g. there is no clustering and backfill.

Disclaimer: I'm the author so I'm a bit biased.