In this paper, we focus on a fundamental biochemical problem of generating 3D molecular conformers conditioned on molecular graphs in a multiscale manner. Our approach consists of two hierarchical stages: i) generation of coarse-grained 3D structure from the molecular graph, and ii) generation of fine atomic details from the coarse-grained approximated structure. For the challenging second stage, we introduce a novel generative model termed Equivariant Blurring Diffusion (EBD), which defines a forward process that moves towards the coarse-grained structure by blurring the fine atomic details of conformers, and a reverse process that performs the opposite operation using equivariant networks. We demonstrate the effectiveness of EBD by ablation studies and comparison to state-of-the-art denoising diffusion models on a benchmark of drug-like molecules.