Analytics Engineer Intern - 8 month contract

Ratehub

1d•$50,000 - $60,000•Remote

About The Position

Ratehub is a unique Canadian Fintech company dedicated to helping Canadians make better financial choices across saving, spending, borrowing, investing, and protecting. Through digital application technology and award-winning brokerages, Ratehub assists over 2 million Canadians monthly in improving their finances. The company operates various businesses including mortgage and insurance brokerages, mortgage origination and servicing, a Financial Services Marketplace, and content across Ratehub and MoneySense. This role is for a top-performing Analytics Engineer Co-op to join the newly created Data Team. This team captures, analyzes, and models data to provide insights to members and businesses, serving as the backbone for all business units. The intern will report to the Lead Data Engineer and contribute to high-impact projects, translating complex data into actionable insights. This is an opportunity to gain hands-on experience with modern BI tools and ensure data integrity and trust. The ideal candidate possesses strong communication skills, an eye for data visualization, and a background in engineering or analytics. They will work closely with senior engineers, analysts, and business stakeholders, providing valuable support through data modeling and validation. Ratehub is a remote-first company, and this position is open to remote candidates for the 8-month co-op term.

Requirements

Currently enrolled in a post-secondary co-op program in Data Analytics, Computer Science, or a related field.
High proficiency in SQL (comfortable with complex joins, window functions, and CTEs).
Familiarity with Power BI, Looker, or BI tool.
Basic understanding of data transformation and testing tools like dbt.
Familiarity with data quality frameworks or automated testing logic for data pipelines.
Simplicity First: You prefer simple, maintainable solutions over over-engineered abstractions.
Effective Communicator: You are comfortable asking questions and providing/receiving candid feedback to ensure project success.
Incremental Delivery: You understand the value of getting a working version into production quickly and iterating based on feedback.
Culture Fit: No Ego: No task is too big or small. You are never afraid to ask questions when you are trying to learn and understand things. You have no problem rolling up your sleeves and helping to execute when the team needs help. This humility extends to all aspects of your work and interaction with teammates.
Player Coach: You mentor and teach as you execute. You model the behaviour you expect from your team. You don’t just tell others what to do, you know and show how to do it at a high standard.
Growth mindset: You have a desire to always continue to grow and learn. This means a willingness to get outside your comfort zone and try new things because you view these as opportunities to gain skills and knowledge.
Helping Hand: You always offer to help without having to be asked. You go the extra mile to help out regardless of your team and function.
Get S##T Done: Your bias is towards action. This means pitching in and rallying to get things across the finish line. Rather than putting off work ask yourself what you can do today to move the needle on a project or goal.
Digs Deep: You aren't afraid to ask questions because you want to understand every issue so that you can properly solve the root cause of the problem instead of just completing the task you are given.

Responsibilities

Play a key role in the transition from Looker to Power BI, recreating essential dashboards and ensuring reporting accuracy across platforms.
Perform data validation between Looker and Power BI to ensure that metrics, logic, and filters remain consistent and accurate.
Assist in developing and maintaining dbt tests (schema and data tests) to catch upstream data quality issues before they reach the reporting layer.
Provide ad-hoc support for existing dashboards, troubleshooting data discrepancies and fulfilling custom visualization requests.
Build clean, documented data models and optimize SQL queries to improve dashboard performance and reduce refresh times.