Gender disaggregation in statistical information on wages, job skills, and occupational choices is necessary to formulate policies to reduce gender gaps in the labor market, particularly in developing countries. In Pakistan, previous research has focused on analyzing the gender wage gap at the national level without using a complex sampling design for the survey. This study fills the gap in two ways. First, it analyzes gender-disaggregated statistics on wages and occupations across small and large urban centers. Second, it uses the gender inequality measurement techniques, i.e., Blinder Oaxaca Decomposition, to quantify the gender wage gaps and compare the gender wage differentials for small and large cities. The study used a complex sample design of a nationally representative survey, the Labor Force Survey (LFS), 2014–2015. Results show a lower gender wage gap in small-sized cities (8%) than prevails in larger cities (31%). The gender gap tends to be more common in the lower tiers of the urban labor market than managerial ranks, and the result holds irrespective of the location of the job. The results highlight the significance of gender disaggregate statistics to monitor progress on the following specific Sustainable Development Goals (SDGs): (1) to eliminate gender discrimination against vulnerable groups by implementing national legislation and international conventions (SDG 5), (2) to reduce the gender wage gap in cities through the identification of loopholes, mainly the lack of gender mainstreaming in work-related policies (SDG 10), and (3) to formulate proactive employment policies to tackle the challenges of urbanization (SDG 11) by increasing employment opportunities and reducing discrimination in small urban centers (Sustainable Kindly check and confirm. Development Goals (SDGs) https://www.un.org/development/desa/disabilities/envision2030.html" xmlns:xlink="https://www.w3.org/1999/xlink">https://www.un.org/development/desa/disabilities/envision2030.html). This study sets new directions for future research.