C-IT-105 Data Analyst  Intern

CAE•Montreal, QC

1d•Hybrid

About The Position

This position is exclusively open to students pursuing a university degree. Internship dates: From August 31st to December 18th 2026. By joining our team, you will have the opportunity to join our new Data and AI Platform department within our team of data specialist / data engineers. You will thus participate in CAE’s Data Strategy and its evolution. Your work will allow CAE to offer better services and develop new products based on data.

Requirements

Strong knowledge of French, English, both written & spoken
Industry experience working with data, coding and scripting (Python/Java/Scala/SQL/JS/Bash), and with Microsoft cloud services: Azure, Databrick, etc is an asset
Experience developing and administering large data systems.
Experience supporting and working with cross-functional teams in a dynamic environment.
Experience with big data tools: Hadoop, Spark, Kafka.
Experience with relational SQL and NoSQL databases, including SQL Server and CosmosDb.
Experience with automated data pipeline and workflow management tools: DevOps, ARM, Data Factory, Airflow.
Experience with Microsoft cloud services: Azure, Databrick.
Experience with stream-processing systems: Storm, Spark-Streaming.
All applicants must be legally entitled to work in Canada and must meet the requirements of the Canadian Controlled Goods Program (CGP).
All hires will be required to complete, sign and return the Controlled Goods Program form within a week of its transmittal.
They must also provide a copy of their passport or birth certificate.
All students with a work permit must provide a copy of it and a police clearance certificate from the country or countries where they have resided in the past five years.

Nice To Haves

Pursuing a bachelor’s or master’s degree in software engineering, Computer Science, or related field with 1 year completed

Responsibilities

Assemble large, complex data sets that meet functional / non-functional business requirements.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics
Keep data separated and secure across national boundaries through multiple data centers.
Be an active member of the business transformation