APTPUO-Fall 2026 -MEM6287B (online)

University of Ottawa•Ottawa, ON

3d•Remote

About The Position

The Faculty of Engineering at the University of Ottawa is seeking a Regular Part-Time Professor to teach the "Advanced Data Analytics (On Line)" course (MEM6287 Section B) during the Fall 2026 semester. This course will cover the fundamentals of Big Data, including big database management (NoSQL) with applications in engineering and management, and review supporting technologies. It will also explore AI concepts for advanced analytics in engineering and management.

Requirements

Bachelor's degree in business or engineering.
Solid industry track record in professional and managerial role(s) related to technology project initiation & development.
In-depth understanding of Big Data Analytics, associated technologies, and use-cases.
In-depth knowledge of common NoSQL database systems such as MongoDB, Cassandra, Kafka, Redis, etc.
Deep understanding of Big Data Analytics tools especially Hadoop and Spark.
Hands-on knowledge of Spark libraries and languages such as PySpark, Scala, and SQL.
Working Knowledge of DataBricks Community Edition.
Knowledge of Big Data Analytics implementations by cloud providers, especially MS Azure.
Understanding of Azure Big Data landscape and tools such as Event Hubs, Azure Data Factory (ADF), Azure Data Lake Sore, Azure Data Lake Analytics, Azure Data Lake Storage, and PowerBI.

Nice To Haves

Master's in management or engineering.
PhD.
Experience as CTO or higher ranking role in engineering management in a technical/technological firm.
Experience in post-secondary teaching and/or professional development instruction.

Responsibilities

Teach the "Advanced Data Analytics (On Line)" course (MEM6287 Section B).
Deliver course content covering Big Data fundamentals, NoSQL database management, supporting technologies, and AI concepts for advanced analytics.
Utilize knowledge of Big Data Analytics, common NoSQL database systems (MongoDB, Cassandra, Kafka, Redis), Hadoop, Spark, Spark libraries (PySpark, Scala, SQL), DataBricks Community Edition, and cloud platforms like MS Azure (Event Hubs, ADF, Azure Data Lake Store, Azure Data Lake Analytics, Azure Blob Storage, PowerBI).