Instructor DASA 3P41 Fall D2

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Post End Date:

June 29, 2026 at 11:59 PMThis job advertisement is to fill an existing vacancy in the CUPE4207-1 (Employee Group)

Storage and Retrieval of Big Data (DASA 3P41 / ITIS 3P41)

Mondays 19:00-22:00

Course Summary

This course focuses on the design and construction of enterprise-level systems for the storage, retrieval, and integration of big data. Students will examine distributed database architectures, data extraction/transformation/loading (ETL), replication, and concurrency control. Key topics include NoSQL, object-oriented, and multimedia databases; advanced query languages; reduction of large datasets; and the use of industry-standard tools for data processing, visualization, and interpretation.

Compensation

Effective September 1, 2026 - $7, per half course (195 hours nominally)
Effective September 1, 2026 - $15, per full course (390 hours nominally)
Please note: Instructors who are employed in a 2-hour/week lecture, or the equivalent of a 2-hour/week lecture, are responsible for the first hour of seminar/lab in each course.

Duties

Duties and responsibilities will be in accordance with Article of the Collective Agreement. These include scheduled contact time with students and non-classroom time (preparation of lectures, student consultation, marking and grading and course administration, including grade appeals and cases of academic dishonesty).

Minimum Qualifications

A Master’s degree (or higher) in one of the following fields:

• Information Systems and Technology

• Computer Science

• Advanced Database Design

• Data Management or a closely related discipline

Required Experience and Skills:

• Demonstrated expertise in big data storage and retrieval architectures, including enterprise data warehouse design and implementation, distributed databases and data replication/concurrency models, and ETL processes and data pipeline development

• Practical experience with NoSQL and object-oriented database systems, multimedia databases and complex data types, and Advanced query languages and dataset reduction techniques

• Proficiency in processing large-scale data using industry-standard tools, packages, or programming frameworks

• Ability to generate and interpret data-driven visualizations for analysis

Preferred Qualifications:

• University-level teaching experience in database systems, information systems, or big data technologies

• Experience in designing and delivering instruction (in-person or online)

• Practical experience with distributed computing frameworks (, Hadoop, Spark), scalable storage technologies (, HDFS, cloud data lakes), data integration and federation tools across heterogeneous systems

• Familiarity with real-world applications of big data systems in industry or research contexts

• Strong analytical and problem-solving background relevant to large-scale data infrastructure

• Evidence of competent and effective teaching experience at the undergraduate university level (letters of reference and course/performance evaluations).