Intern, Data Analytics Engineering at Capital One
Toronto, ON, Canada -
Full Time


Start Date

Immediate

Expiry Date

20 Nov, 25

Salary

0.0

Posted On

20 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Aws, Git, Sql, Mathematics, Computer Science, Communication Skills

Industry

Information Technology/IT

Description

BASIC QUALIFICATIONS:

  • Will obtain a Bachelor’s degree or higher between January 2026 and September 2027

PREFERRED QUALIFICATIONS:

  • Pursuing a Bachelor’s degree in Mathematics, Computer Science, Engineering, or another quantitative discipline with a strong programming background
  • Familiarity with SQL and/or data transformation tools such as dbt. Python experience would also be an asset
  • Experience building and maintaining data pipelines
  • Ability to shape and develop requirements into practical solutions
  • Ability to clearly explain technical terms to a non-technical audience
  • Experience in a Unix/Linux environment, with Git, AWS, or APIs
  • Excellent verbal and written communication skills
  • Previous intern experience

How To Apply:

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Responsibilities

As a Data Analytics Engineering Intern, you will work with cross-functional teams to develop tools and data structures. As a creative problem-solver, you will be challenged to consider multiple options and select the optimal solution to meet the needs of your customers. You will own the recommendation and resolution to an existing business problem and will be involved end to end, from problem identification to solution deployment.

Your Responsibilities:

  • Transform data into data structures in our data lake and Snowflake data warehouse that are leveraged for business decision making
  • Create, enhance and maintain critical data processes
  • Act as a steward for our data: ensuring it is high quality, trustworthy, well documented, and easy to use
  • Build, automate, and maintain critical business reporting and visualizations that helps deliver insights
  • Perform investigative analysis on large/diverse dataset
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