Adjunct Lecturer, Fundamentals of Data Engineering (On-Campus, Fall '26)
This adjunct role at Columbia University requires experienced professionals to teach graduate students the principles of data engineering, emphasizing bridging gaps between analytic teams and technology partners. The focus is on hands-on instruction in data management, pipelines, and collaborative techniques to ensure data is leveraged effectively.
Skills required
About this role
Columbia University’s Master's in Applied Analytics program seeks experienced industry professionals to serve as a part-time Lecturer for a graduate-level course in Managing Data.
The Fundamentals of Data Engineering 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
Lead class lectures, instructional activities, and classroom discussion. Attend all class sessions.
Monitor and address student concerns and inquiries.
Evaluate, grade student work and assessments.
Conduct office hours.
Qualifications
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
Doctoral degree or equivalent required, 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 of SQL and NoSQL databases.
Knowledge of Python and Spark.
10+ years of related applied professional experience.
Preferred Skills & Experience
Knowledge of MapReduce strongly desired.
Other software or programming languages like R and Tableau.
Statistical and Machine learning knowledge.
University teaching experience.
Additional Information
Salary range: $11,000 - $13,000 per semester long course
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 Employer / Disability / Veteran
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