  We study SDE $$ d X_t = b(X_t) \, dt + A(X_{t-}) \, d Z_t, \quad X_{0} = x
\in \mathbb{R}^d, \quad t \geq 0 $$ where $Z=(Z^1, \dots, Z^d)^T$, with $Z^i,
i=1,\dots, d$ being independent one-dimensional symmetric jump L\'evy
processes, not necessarily identically distributed. In particular, we cover the
case when each $Z^i$ is one-dimensional symmetric $\alpha_i$-stable process
($\alpha_i \in (0,2)$ and they are not necessarily equal).
  Under certain assumptions on $b$, $A$ and $Z$ we show that the weak solution
to the SDE is uniquely defined and Markov, we provide a representation of the
transition probability density and we establish H{\"o}lder regularity of the
corresponding transition semigroup.
  The method we propose is based on a reduction of an SDE with a drift term to
another SDE without such a term but with coefficients depending on time
variable. Such a method have the same spirit with the classic characteristic
method and seems to be of independent interest.
