This paper proposes a multi-level decoupled method for optimizing the structural design of a wind turbine blade. The proposed method reduces the design space by employing a two-level optimization process. At the high-level, the structural properties of each section are approximated by an exponential function of the distance of that section from the blade root. High-level design variables are the coefficients of this approximating function. Target values for the structural properties of the blade are determined at that level. At the low-level, sections are divided into small decoupled groups. For each section, the low-level optimizer finds the thickness of laminate layers with a minimum mass, whose structural properties meet the targets determined by the high-level optimizer. In the proposed method, each low-level optimizer only considers a small number of design variables for a particular section, while traditional, single-level methods consider all design variables simultaneously. The proposed method converges to the optimum solution faster for a problem with a large number of design variables, because it divides the design space into multiple subspaces, each containing a small set of design variables. The efficiency of the proposed method is demonstrated on a turbine blade, by comparing it with a traditional single-level method.