Our research paper investigates the relationship between engineering graduate student funding, demographics, initial employment, and future career sector. Although a growing number of students have earned engineering doctorates over the past decade and over 10,000 students received engineering doctorates in 2015 (National Science Board, 2018a), there exists a gap in the literature regarding this student population. Unlike other STEM fields, where a doctoral degree serves as a key step in pursuing an academic path, engineering PhDs have a greater split between industry and academia, which we categorized as Industry and Education for future career sector. Students on Teaching Assistantships or Research Assistantships gain different experiences that may help them in different employment sectors. We categorized the five primary funding mechanisms as Research Assistantship, Fellowship, Teaching Assistantship, Personal Earnings, and Other. Initial Employment is categorized as Unemployed, Temporary, and Employed. Our research questions are: 1) What are the 3-year and 6-year career sector breakdowns for engineering doctoral recipients by gender and race? 2) How, if at all, do graduate student funding mechanism, gender and race, and initial employment predict future career sector 6 years after receiving an engineering doctorate? Using NSF's Survey of Doctorate Recipients (SDR) and Survey of Earned Doctorates (SED) data, we analyzed relationships between engineering doctoral recipient primary funding mechanism and career sector at a timepoint of 5 to 6 years after receiving their degree. We matched populations between the two surveys and the resulting dataset consisted of 5682 engineering doctoral recipients who received their degrees between 1997 and 2014. We used descriptive statistics and step-wise logistic regression models with primary funding, gender and race, and initial employment as predictors to explore the research questions. Descriptive statistics indicate female students enter Education as a career sector in higher proportions than men 2 to 3 years after receiving their degree, while male students enter Industry in higher proportions than women. White, Asian, and International students are more likely to be employed in Industry 5 to 6 years after receiving their degree, while Black and Hispanic students are more likely to be employed in Education. The final logistic regression model with funding, gender and race, and employment type as predictors showed Hispanic, Asian, Temporary, and Employed as statistically significant. It is important to understand how student experiences in grad school prepare students for future careers and whether opportunities are presented equitably. Future work includes understanding student interests at the start and end of graduate school and whether funding type influences career goals and interests. [ABSTRACT FROM AUTHOR]