Bayesian causal inference

I am new to PYMC3 and Bayesian inference. I have sifted through the internet to find practical examples of how to do causal inference (on observational data) with PYMC3. Is it possible to encode a complex causal DAG in PYMC3 and then perform interventions to ask causal questions?
It seems like this would be the ultimate business use case for any data analysis method for observational data (of which many businesses have tons of data).
I have never found practical tutorials or examples on combining causal inference with Bayesian techniques. Is there a resource you can point me to, where I can learn how to use PYMC3 to achieve the above goal?

The second edition of Richard McElreath’s Rethinking was just released and it focuses on combining causal inference and Bayesian methods, so I’d really advise it. We are currently porting the code to python and PyMC3.
Stay safe :v: