Does delta sigma ADC reduce gaussian noise on input to ADC or quantization noise only

The motive for posing this questions arises from a difference of analysis between a colleague and myself.

Our general environment is in the construction of an analog front end which takes in signals to an instrumentation amp in the low microvolt range. followed by a gain stage, which then feeds a 24 bit delta sigma converter.

My understanding is that we can achieve a certain number of noise-free bits from the ADC, where the noise is the quantization noise. For any gaussian noise on the input to ADC, this noise will not be reduced by the ADC itself. And in this regard, we need to do some additional averaging of the sampled data points for reducing the gaussian noise as an additional processing step.

My colleague thinks that the delta sigma ADC will also reduce the gaussian noise on the input signal, and therefore additional averaging is not needed.

As a second question, is it the case that we should arrange the gain so that as much of the signal fills the dynamic range of the ADC so as to improve the SNR of the signal due to having a large signal quantized as a function of quantization noise. In other words, the quantization noise is a smaller fraction of the signal?

Could you help us out by commenting on this question?

The DS ADC(delta sigma ADC) output will be equal to the input*STF(signal transfer function) + quantization error*NTF(noise transfer function). At the output, the data needs to passed through a low pass filter to filter out the shaped noise. In most practical cases, the STF is almost one in the signal bandwidth. Thus, there is no filtering of the noise from the input. But if the STF is designed to have a low pass behaviour, my guess is that it will reduce the noise.

Yes the ADC input range should be maximized to get as much dynamic range one can obtain.