Four candidates describe Shopify's Data Engineer interviews: a recruiter screen, SQL coding or pair programming, then streaming, data modeling, or ETL deep dives. Here is what each reported and how to prepare.
$135K
Avg. Base Comp
$187K
Avg. Total Comp
Not reported
Typical Rounds
1-2 months
Process Length
Candidates describe a SQL-heavy process at Shopify, but the details differ from person to person. The common starting point is a recruiter or HR conversation. After that, one candidate reports a timed SQL coding round in CoderPad where speed mattered, and a second describes pair programming with an engineer that focused on window functions and self-joins. A third says the SQL questions were on the easier side, covering joins and aggregations. A fourth recalls a pair programming exercise and a SQL round on aggregations, joins, and date handling, plus a rolling-average problem.
Beyond SQL, the reports point to deep dives tied to real work. One candidate was asked to present a recent streaming project and also got a system design discussion on streaming, and said mixing up a few streaming concepts hurt them. Another was given a real problem about optimizing a data model for an end use case and said the interviewer cared about reasoning more than a perfect answer. A third reported ETL pipeline design, keeping pipelines reliable, and a question on optimizing a SQL pipeline for large-scale processing with data quality checks. That candidate found Docker and Kubernetes the hardest part.
Two candidates mention a data model design or behavioral round, and one reports an online assessment before interviews. Outcomes were mixed: one candidate accepted an offer and three did not receive one. One of those three described slow scheduling and no follow-up after the final round. Prepare by practicing SQL quickly, stating assumptions such as date formats aloud, and being ready to explain a pipeline or streaming project you built, including the data model and tradeoffs.
Synthesized from 4 candidate reports by our editorial team.
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Real interview reports from people who went through the Shopify process.
The process was harder to navigate than the interviews themselves. Scheduling was incredibly difficult—I had to keep pushing the recruiter just to get things scheduled, and even then they couldn't tell me who I'd actually be working with or provide any real insight into the team. For a company of Shopify's size, that lack of transparency was honestly surprising.
When I finally got through the rounds, there was a recruiter screening followed by pair programming with an engineer. That's where they really tested SQL fundamentals—window functions and self-joins specifically. Then there's a technical deep dive where they present you with a real problem and ask how you'd solve it; in my case, it was about optimizing a data model for an end use case. It wasn't about finding the perfect answer as much as explaining your reasoning. They also have a behavioral or "about you" round that runs about an hour, where it felt more conversational.
The whole timeline stretched across a couple of months. I made it through what I thought was my final round and then... silence. No offer, no rejection, just nothing. They never followed up. My take is they'd made their decision, but apparently couldn't be direct about it. It's one of those experiences that sticks with you not because I didn't get the job, but because of how the whole thing was handled.
Prep tip from this candidate
Master SQL window functions and self-joins for the pair programming round, and prepare concrete examples of data model optimization—they want to see how you think about scaling and tradeoffs.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Shopify
Write a query to get the total three-day rolling average for deposits by day
| Question | |
|---|---|
| Merge Sorted Lists | |
| Prime to N | |
| Upsell Transactions | |
| Paired Products | |
| Alphabet Sum | |
| Identifying User Sessions | |
| Total Spent on Products | |
| One Element Removed | |
| Resumable Fact Table Load | |
| Clickstream Data | |
| Hurdles In Data Projects | |
| Priority Queue Using Linked List | |
| Move Zeros Back | |
| Click Data Schema | |
| Walking Robot | |
| A/B Testing a Checkout Button Change | |
| Possibly Biased Coin | |
| Pop Tail | |
| String Palindromes | |
| Messenger Service Design | |
| Merchant Dashboard Design | |
| International e-Commerce Warehouse | |
| Filling Supermarket Bag | |
| Yelp-like System | |
| Liker's Likers | |
| Text Editor With OOP | |
| Fixed-Length Arrays: Deletion | |
| External Sorting | |
| Client Solution Pushback |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report an initial recruiter or HR conversation about background, motivation for the role, and how the process works. One candidate also reports an online assessment before any interviews, and that the invitation depended on the result. Scheduling may be slow, as one candidate had to keep following up.
Candidates report a SQL-focused technical round, described as CoderPad coding or pair programming with an engineer. Topics reported include joins, aggregations, window functions, self-joins, date handling, and a rolling-average problem. One candidate says speed mattered, and another says the questions were easier. Expect to explain your assumptions and approach.
Candidates describe deep dives built on real scenarios: presenting a recent streaming project with system design, optimizing a data model for an end use case, or ETL and SQL pipeline design with data quality checks. One candidate also faced Docker and Kubernetes questions. Interviewers appear to value clear reasoning over memorized answers.
Two candidates mention rounds beyond the technical screens. One reports a data model design discussion based on business processes, and another reports a roughly hour-long conversational about-you round. Not every candidate describes these rounds, so the exact sequence may vary. Outcomes ranged from an accepted offer to silence after the final round.
