APTPUO-Fall 2026 -MEM6287A (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 for the course MEM6287A, Advanced Data Analytics (Online), during the Fall 2026 semester. This course covers the fundamentals of Big Data and NoSQL database management with applications in engineering and management, including supporting technologies and AI concepts for advanced analytics. The position is limited to a Regular Part-Time Professor.

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 Blob Storage, and PowerBI.

Nice To Haves

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

Responsibilities

Deliver instruction for the Advanced Data Analytics course (MEM6287A) online.
Manage Big Data and NoSQL database concepts with applications in engineering and management.
Incorporate AI concepts for advanced analytics in engineering and management.
Utilize and teach about Big Data Analytics, associated technologies, and use-cases.
Teach common NoSQL database systems such as MongoDB, Cassandra, Kafka, Redis.
Instruct on Big Data Analytics tools, specifically Hadoop and Spark.
Provide hands-on knowledge of Spark libraries and languages like PySpark, Scala, and SQL.
Guide students on using DataBricks Community Edition.
Explain Big Data Analytics implementations by cloud providers, particularly MS Azure, including Event Hubs, Azure Data Factory (ADF), Azure Data Lake Store, Azure Data Lake Analytics, Azure Blob Storage, and PowerBI.