The process took 3 weeks. I interviewed at Shopify in Aug 2021
Interview
The interview comprises three parts:
- "Your Story"
- ~60 minute Technical
- On-Site (~3-5 more interviews, including more technicals)
I was rejected after the first technical.
The first portion is nothing to worry about. It's an internal recruiter or someone who works tangentially to the relevant team. They're looking for relevant experience, personal red flags, and generally getting you excited for the role.
Second interview was a remote call where I was asked to use my own IDE to create a solution to a technical problem.
What probably took me out of consideration was that I focused too much on the wrong part of the question, wasting 10-20 minutes. Otherwise, it should have been fairly simple.
Rejected after this.
Interview questions [1]
Question 1
Using a language of your choice, create a clone of the `tail` command line tool's default functionality.
Expand upon it by including a handful of the optional parameters with
First step was recruiter screen. After that it's a 1 hour SQL pairing exercise. For the SQL Screen, you are encouraged to use AI and it is done through Coderpad
Interview questions [1]
Question 1
First two questions are relatively straightforward with aggregations. The third question involves a cross join with a date spine. Basically you have some activities on certain dates, and need to fill in the activity count on missing dates with 0. I did not get a chance to look at the fourth question.
first round is recruiter, followed by a senior engineer, and then data engineer (pair programming round). after this is the classic shopify 'about you' round which is 1 hour long
I applied through a recruiter. The process took 3 weeks. I interviewed at Shopify (Toronto, ON) in Oct 2025
Interview
The interview process was collaborative, well structured, and engaging throughout. The interviewers encouraged open discussion, asked thoughtful and practical questions, and fostered a supportive environment. They focused on real-world scenarios, problem-solving skills, and past experiences, making the conversation feel natural, professional, and insightful rather than purely evaluative.
Interview questions [1]
Question 1
Can you explain how you would design and optimize a SQL-based data pipeline to handle large-scale data processing and ensure data quality?
