Computing shifted signal without first reconstructing
Because the sampling frequency is above the Nyquist rate, the original signal can be written in terms of its samples $y(n)$:

$$x(t)=\sum_{m=-\infty}^{\infty}y(m)\frac{\sin[\pi(t-mT)/T]}{\pi(t-mT)/T}\tag{1}$$

By setting $t=nT+T/2$ you get from (1)

$$z(n)=\sum_{m=-\infty}^{\infty}y(m)\frac{\sin[\pi(n-m)+\pi/2]}{\pi(n-m)+\pi/2}$$

and since

$$\sin[\pi(n-m)+\pi/2]=(-1)^{n-m}$$ you finally get

$$z(n)=\sum_{m=-\infty}^{\infty}y(m)\frac{(-1)^{(n-m)}}{\pi(n-m)+\pi/2}$$

So for computing $z(n)$ you do not need to reconstruct $x(t)$ but you need to compute a sum over all values $y(m)$. In practice a few samples $y(m)$ around the value $n$ will be sufficient because the weighting factors in the sum decrease with increasing distance $|n-m|$.