It is important to accurately estimate the impact of flow and geometric variations for engineering design and manufacture. In this paper, an efficient uncertainty quantification analysis framework based on the combination of Universal Kriging (UK) metamodels and sparse Polynomial Chaos Expansion (PCE) is proposed. A challenging analytical test function and an engineering test are considered to investigate the response performance of the UK-PCE method. Then, this method was applied to the uncertainty quantification on the aerodynamic and heat transfer performance of GE-E3 rotor blade squealer tip. Meanwhile, a global parameter sensitivity analysis using the Sobol Indice method is carried out to identify the key parameters for the aerothermal performance of the squealer tip. Wherein, the inlet total temperature is considered as flow condition uncertainty parameters and tip clearance and cavity depth are considered as geometrical uncertainty parameters. The results show that the UK-PCE method reduces the computational cost by more than 70% in comparison to the typical PCE method. Under the influence of the uncertain geometry and operating conditions, the heat flux of the squealer tip basically conforms to the normal distribution and the statistical mean value of it increased by 5.32% relative to the design value and the probability of it deviating from the design value by 5% is as high as 44.62%. The result of sensitivity analysis reveals that the uncertainty of the aerodynamic characteristics of the squealer tip is almost entirely caused by the tip clearance which accounts for 90.31% and 98.77% of the variance of the leakage flow rate and total pressure loss coefficient. And it is also a key variable for the uncertainty of the heat transfer performance considering that its variance indexes for tip heat flux and blade heat flux are 31.23% and 73.14%, respectively. Finally, the influence mechanisms of the uncertainty parameters on the aerothermal performance of the squealer tip are investigated by detailed flow and thermal field analysis.