The construction of a perfect employment guidance system is an inevitable choice to adapt to the current employment situation in colleges and universities, and the Internet and big data technology provide important support and opportunity for this. In this paper, the C4.5 algorithm is used to calculate the information entropy and information gain rate of students’ performance and employment-related data, realize the accurate portrayal of the employment portrait of higher education students, and realize the recommendation of employment-related information based on the classification decision tree. Then we design the platform for higher education student counseling and employment guidance using the Hadoop MapReduce software framework. The platform’s concurrency performance is good, and the stress test pass rate is 100%, as shown by the results. After the application of the Higher Education Student Counseling and Career Guidance Platform, the satisfaction of job search skills in the post-test was significantly higher than that in the pre-test (t=5.236, P=0.042<0.05), which indicates that the platform is very effective in intervening in students’ career planning and core strengths. It is also found that the platform is able to realize accurate portrayal and recommendation of portrait and employment information, from which students can obtain information that is helpful for employment and have a high level of satisfaction with it. The platform designed in this paper can provide more accurate and efficient services for employment guidance of college students and help them achieve their career development goals.