Adjunct Associate Faculty, Fundamentals of Data Engineering (On-Campus, Fall '26)

Columbia University has been a leader in higher education in the nation and around the world for more than 250 years. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds to pursue greater human understanding, pioneering discoveries, and service to society.

The School of Professional Studies at Columbia University offers innovative and rigorous programs that integrate knowledge across disciplinary boundaries, combine theory with practice, leverage the expertise of our students and faculty, and connect global constituencies. Through seventeen professional master's degrees, courses for advancement and graduate school preparation, certificate programs, summer courses, high school programs, and a program for learning English as a second language, the School of Professional Studies transforms knowledge and understanding in service of the greater good.

Seeking analytics professionals to serve as a part-time Associate for a graduate-level course on Managing Data. An Associate is a faculty line junior to a Lecturer, that provides subject matter expertise and supports the instructional process for a course section. Serving as an Associate is an outstanding way to gain exposure to graduate-level teaching at Columbia University.

The Managing Data course provides students with a foundational context for managing data so that it can be leveraged and used with confidence. Analytic teams work closely with technology partners in managing data. Languages and techniques unique to each team can impede cooperation. To bridge this gap, this course provides a broad overview of data technology concepts including database engines and associated technologies and exposes students to foundational data principles, governance processes and organizational prerequisites needed to overcome challenges to ensure data quality. 

Responsibilities

• Attend all class sessions, assist with instruction, lead breakout sessions, facilitate discussions.

• Evaluate, grade student work and assessments as requested by the course Lecturer.

• Monitor and address student concerns and inquiries.

Columbia University SPS operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting. 

Requirements

• Graduate degree in an area related to data science, statistics, computer science or another discipline that provided rigorous training in quantitative analytics.

• Knowledge of databases, topics in Big Data, and Data Analysis.

• Knowledge in SQL and NoSQL databases.

• 3+ years of related applied professional experience.

Preferred Skills & Experience

• Knowledge of MapReduce, Spark strongly desired.

• Other software or programming languages like R, Python, Tableau

• Statistical and Machine learning knowledge.

• University teaching experience.

Please submit a resume inclusive of university teaching experience.

All your information will be kept confidential according to EEO guidelines.

Columbia University is an Equal Opportunity/Affirmative Action employer.