Using DFT Circular convolution property I am trying to make proper use of the circular convolution property of DFT.
I was taught that the DFT of x[n]*CircularConv*y[n], would be equal the product of the individual DFT's X[k],Y[k].

On the problem im trying to solve, the signal x[n] is convolved (Circular convolution) with the discrete impulse response y[n] to produce the output signal z[n].   (x[n]*y[n]=z[n])
Having the signals z[n],y[n]+their DFT's, and using the property mentioned above,
can I conclude that X[k]=Z[k]/Y[k] immediately? are there any limitations? or am I doing it totally wrong?
Yes, that conclusion would be valid. However, as you suspected, there are some limitations. Consider the case where the system's frequency response $Y[k]$ contains one or more zeros. In that case, corresponding frequency bin in your estimate of the input signal $X[k]$ would diverge to infinity (because of the division by zero).

What you're really trying to perform by doing this sort of calculation is deconvolution, which is a complex topic in itself, but suffice it to say that deconvolution is often difficult; you illustrated one of the reasons why. This naive approach of just dividing in the frequency domain is known as a zero-forcing type of algorithm.