Hi @ari_sh70,
This would be my current approach within the QIIME 2 environment. With the upcoming DADA2 release, I would probably switch to that since at least that will have some benchmarks to back it up.
Another caveat you should be aware of is that Deblur tends to drop more reads as their length increases, see an example calculation here. So, if you find yourself losing too many reads after Deblur, maybe consider just using your forward reads only, you would lose some resolution but may retain many more reads. This would ultimately be based on what your overall goals are with the analysis and what you prioritize.
Having never used trimmomatic, I'm not sure what aspects of this approach would be better over the approaches I mentioned above, or with q2-vsearch if you rather not use the denoisers. Can you expand on what your plan would be?