For the very limited situation in which $k=1$ and we're only interested in functions whose domain is $\{0,1\}^n$, the VC dimension is $\lfloor \log_2(n+1) + 1 \rfloor$.
The upper bound follows essentially from Sasho's argument: there are $2+2n$ 1-juntas on $n$ variables, and if there were more than $\log_2$ of that many inputs, we could find a function that avoids all 1-juntas.
To see the lower bound, consider the matrix whose columns contain the $2^{\lfloor \log_2(n+1) \rfloor} - 1 \le n$ not-all-zero bitstrings of length $\lfloor \log_2(n+1) \rfloor + 1$ that start with a zero. The inputs to shatter are the rows of this matrix (padded up to length $n$). Every function of these inputs is either constant, or else it or its negation appears as a column, so it's computed by a 1-junta.
Here's an example for the case $n=7$ which illustrates the general idea. The claim is that the VC dimension of $1$-juntas on $7$ bits is $4$. Consider the matrix
$$\begin{array}{ccccccc}
0&0&0&0&0&0&0\\
1&0&0&0&1&1&1\\
0&1&0&1&0&1&1\\
0&0&1&1&1&0&1
\end{array}$$
formed by setting the columns to be all the length-$4$, not-all-zero bit strings that start with a zero. The claim is that the rows of this matrix are shattered by 1-juntas.
To see this, let $f$ be any boolean function of the rows. We can regard $f$ as a column. Now observe that either $f$ is constant, or else $f$ or its negation appears as some column in the matrix, simply by virtue of how we defined the matrix. In the first case, $f$ is obviously a 1-junta. In the latter case, suppose $f$ appears as column $i$, and observe that we can therefore compute $f$ as just the $i$-th dictator function. It follows that $f$ is again a 1-junta. A similar argument works when the negation of $f$ appears as a column--we represent $f$ by the negation of the $i$-th dictator. Thus in every case $f$ is a 1-junta. Since $f$ was arbitrary, it follows that the set formed by the rows of the above matrix is shattered by 1-juntas.
This idea can in theory be extended to larger $k$, where you encode every function as some $k$ columns in the matrix. I don't see how best to argue this at the moment, though.