Assuming you do seek the third-moment skewness and assuming independence, the third central moment of $X_1-X_2$ is
\begin{eqnarray}
E[((X_1 - X_2) - (\mu_1-\mu_2))^3 ]&=&E[(X_1 - \mu_1 - (X_2 -\mu_2))^3 ]\\\\
&=& E[(X_1-\mu_1)^3] - 3E[(X_1-\mu_1)^2]E(X_2-\mu_2) \\\\
& & \qquad + 3E(X_1-\mu_1)E[(X_2-\mu_2)^2] - E[(X_2-\mu_2)^3]\\\\
&=& E[(X_1-\mu_1)^3] - 0 + 0 - E[(X_2-\mu_2)^3]\\\\
&=&\sigma_1^3 (1-2p_1)/\sqrt{n_1p_1(1-p_1)}
\\\\
& & \qquad-\hspace{1mm}\sigma_2^3 (1-2p_2)/\sqrt{n_2p_2(1-p_2)}\\\\
&=&n_1p_1(1-p_1) (1-2p_1) \hspace{1mm} - \hspace{1mm} n_2p_2(1-p_2) (1-2p_2)
\end{eqnarray}
The variance of $X_1-X_2$ is
$$\sigma_1^2+\sigma_2^2= n_1p_1(1-p_1)+n_2p_2(1-p_2)$$
Hence (if I made no errors) the skewness should be
$$\frac{n_1p_1(1-p_1) (1-2p_1) -n_2p_2(1-p_2) (1-2p_2)}{[n_1p_1(1-p_1)+n_2p_2(1-p_2)]^{\frac{3}{2}}}$$