This study investigates the intricate relationship between pivotal economic indicators and employment outcomes across various quantiles of the employment distribution within G7 nations, with the objective of elucidating the heterogeneous impacts of these factors on employment. Employing quantile regression analysis, the research assesses the effects of GDP growth, Foreign Direct Investment (FDI), inflation, interest rates, Research and Development (R&D), and trade on employment at distinct quantiles (0.05, 0.25, 0.50, 0.75, and 0.90) of the employment spectrum. This methodological approach allows for a deeper understanding of how these economic determinants exert differential influences across both high-wage and low-wage sectors. The findings reveal that GDP, FDI, and R&D significantly stimulate job creation, especially within high-employment sectors, whereas the effects of inflation and interest rates are more nuanced, benefiting low-employment sectors in some instances but adversely impacting high-employment sectors due to rising costs and reduced investment. Unemployment consistently diminishes job opportunities across all employment quantiles, with its most pronounced effects felt in low-employment sectors. This study makes a novel contribution to the existing literature by utilizing quantile regression to provide a more granular understanding of how economic variables influence labor market outcomes across diverse segments. It underscores the necessity for targeted economic policies designed to address the specific needs of both high- and low-employment sectors, offering critical insights for policymakers aiming to cultivate inclusive and resilient labor markets.