The persistent issue of unemployment and "job-skills mismatch" continues to challenge the local labor market in San Jose del Monte, Bulacan. Despite the availability of vacancies, the reliance on manual referral processes, such as physical logbooks and walk-in applications, often leads to prolonged search times for applicants and unfilled positions for employers. This study aimed to address this gap by developing "SKILL CONNECT: A Local Employment Referral System Utilizing Job Matching Algorithm." The primary research goal was to automate the profiling and matching process to improve efficiency and data security. The system was developed using the Agile Methodology, allowing for iterative improvements throughout the development lifecycle. To ensure software quality, the system was evaluated using the ISO 9126 standard metrics: Functionality, Reliability, Usability, Efficiency, and Portability. A quantitative assessment was conducted with a respondent group comprised of local Job Seekers and Employers using a 5-point Likert scale.