I try to give my input from a methodical approach. From your above computations, we can see that:
For $\lambda = 0$, these eigenvectors $\{v_1,v_2\}$ span the eigenspace $E_{\lambda=0}$:
\begin{Bmatrix}
\begin{bmatrix}
-1\\
1 \\
0
\end{bmatrix},
\begin{bmatrix}
-1\\
0 \\
1
\end{bmatrix}
\end{Bmatrix}
and for $\lambda = 3$, this eigenvector $\{v_3\}$ span the eigenspace $E_{\lambda=3}$:
\begin{Bmatrix}
\begin{bmatrix}
1\\
1 \\
1
\end{bmatrix}
\end{Bmatrix}
These eigenvectors are linearly independent. However, there are repeated eigenvalues for $\lambda = 0$. Next, we check $\langle v_1, v_2 \rangle$. We observe that these eigenvectors are not orthogonal, as what you have shown $\langle v_1, v_2 \rangle =1\neq0$.
Hence, we can use Gram-Schmidt orthogonalization to obtain our orthonormal set.
For $E_{\lambda=0}$, we find our orthonormal vectors $\{e_1, e_2\}$:
\begin{align}
u_1 & = v_1 \\
e_1 & = \frac{u_1}{||u_1||} = \frac{1}{\sqrt2}
\begin{bmatrix}
-1\\
1 \\
0
\end{bmatrix} \\ \DeclareMathOperator{\proj}{proj}
& \\
u_2 & = v_2 - \proj_{u_1} (v_2) \\
& = v_2 - \langle v_2, u_1\rangle u_1\\
& =
\begin{bmatrix}
-1\\
0 \\
1
\end{bmatrix} -
\left\langle
\begin{bmatrix}
-1\\
0 \\
1
\end{bmatrix},
\frac{1}{\sqrt2}
\begin{bmatrix}
-1\\
1 \\
0
\end{bmatrix}
\right\rangle
\frac{1}{\sqrt2}
\begin{bmatrix}
-1\\
1 \\
0
\end{bmatrix} \\
& =
\begin{bmatrix}
-1/2\\
-1/2 \\
1
\end{bmatrix} = \frac{1}{2}
\begin{bmatrix}
-1\\
-1 \\
2
\end{bmatrix} \\
e_2 & = \frac{u_2}{||u_2||} = \frac{1}{\sqrt6}
\begin{bmatrix}
-1 \\
-1 \\
2
\end{bmatrix} \\
\end{align}
For $E_{\lambda=3}$:
\begin{align}
u_3 & = v_3 \\
e_3 & = \frac{u_3}{||u_3||} =
\frac{1}{\sqrt 3}
\begin{bmatrix}
1 \\
1 \\
1
\end{bmatrix}
\\
\end{align}
Hence,
$$
\begin{align}
Q & = [e_1 \space e_2 \space e_3]
=
\begin{bmatrix}
-1/ \sqrt2 & -1/ \sqrt6 & 1/ \sqrt3\\
1/ \sqrt2 & -1/ \sqrt6 & 1/ \sqrt3\\
0/ \sqrt2 & 2/ \sqrt6 & 1/ \sqrt3\\
\end{bmatrix}: \\
D &
=
\begin{bmatrix}
0 & 0 & 0 \\
0 & 0 & 0 \\
0 & 0 & 3 \\
\end{bmatrix}
\end{align}
$$