Snowflake Interview Questions — Page 9

Snowflake·Data Scientist·Technical Phone Screen

Jun 2026

Technical screen for a Data Scientist role at Snowflake. The whole thing was one big multi-part question combining BigQuery SQL, cohort analysis, and a Streamlit app build. Dense and exhausting, but kind of interesting if you're into that stuff.

Write a single BigQuery query using window functions with PARTITION BY that produces a cohort retention heatmap table with columns for signup week, week index, country, cohort size, retained users, and retention rate. Explain how you avoid double-counting users across weeks and handle users with late-arriving events.
Extend the cohort retention SQL to compute weekly ARPU by cohort and country, ensuring users with no purchases still count in the cohort size but contribute zero to revenue.
Build a Streamlit app that lets a user filter by country and toggle between a retention heatmap and an ARPU line chart, treats missing future weeks as NA rather than zero, masks cohorts below 50 users, and includes a UTC offset selector that re-buckets events by timezone without duplicating users across weeks.
Describe two data quality checks you would build into the app, such as verifying cohort size monotonicity across observed weeks and guarding against clock skew that produces negative week index values.

“This is the kind of question where you feel fine until you actually try to write it.”

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Snowflake·Software Engineer·Technical Phone Screen

Jun 2026

Snowflake software engineer interview with a classic sliding window problem that had a tricky follow-up tacked on at the end. Pretty standard algorithmic round but the Unicode angle threw me a bit.

Given a string and an integer k, find the length of the longest contiguous substring containing at most k distinct characters. Implement an O(n) sliding window solution and walk through time and space complexity.
Modify your solution to return the actual substring instead of just its length, and handle Unicode grapheme clusters correctly.

“I got the core solution down pretty quick.”

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Snowflake·Software Engineer·Technical Phone Screen

Jun 2026

Snowflake SWE interview with a tree problem that had a decent follow-up. The core question was manageable but the follow-up pushed into greedy/DP territory which is where things got more interesting.

You're given a rooted tree where some nodes are marked as deleted. A deleted node and everything below it that's now disconnected from the root is removed. Compute the height of the resulting tree, where height is the max number of nodes on any root-to-leaf path. If the root itself is deleted, return 0.
Follow-up: given an integer K, what is the minimum number of additional nodes you need to delete so that the height of the effective tree is at most K? You can delete any nodes you want.

“Pretty standard DFS once you frame it right.”

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Snowflake·Software Engineer·Onsite - System Design / Architecture

Jun 2026

Snowflake system design round for a software engineer role. The whole thing was one big open-ended prompt and you had to drive it yourself, which sounds fine until you're actually in it and realize how much ground they expect you to cover.

Design a distributed system to meet an open-ended product requirement, covering everything from assumptions and SLAs to data modeling, sharding, replication, consistency trade-offs, failure handling, observability, and deployment.

“This was basically a gauntlet.”

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Snowflake·Software Engineer·Technical Phone Screen

Jun 2026

Snowflake SWE technical phone screen with a tree problem that looked manageable until the deleted-node splicing requirement showed up. Single coding question, pretty focused session.

Given an n-ary tree where each node has a boolean 'deleted' flag, compute the maximum height of the effective tree after splicing out all deleted nodes. A deleted node's children get re-attached to its nearest non-deleted ancestor. The root itself may be deleted, and chains of consecutive deleted nodes should collapse entirely. Solve this in a single DFS.

“My first instinct was to build the effective tree explicitly and then measure height separately.”

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Snowflake·Data Scientist·Technical Phone Screen

Jun 2026

Snowflake data scientist interview that went way deeper into finance fundamentals than I expected. The whole thing centered on one long multi-part question about cash flow vs net income, and I genuinely was not prepared for how granular it got.

An asset-heavy company shows rising net income but negative free cash flow for three consecutive quarters. Walk through why FCF can be a better signal than net income for valuation, solvency, and dividend safety, and reconcile the two numerically including non-cash charges, working capital changes, and capex.
Give at least two specific situations where net income looks healthy but free cash flow is signaling real risk. Also describe one scenario where FCF itself can be temporarily misleading.
If you could only access one financial statement, which would you pick for each of these three goals: assessing credit risk, evaluating profitability trends, and estimating cash runway? For each choice, name three critical risks or gaps you can't assess without the other statements, and explain how you'd approximate them.

“I fumbled the numeric reconciliation part.”

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Snowflake·Software Engineer·Technical Phone Screen

Jun 2026

Snowflake software engineer interview with a tree-based coding problem and two follow-ups that escalated pretty fast into concurrency territory.

Given a tree, compute the sum of values across its subtrees and store the results in a new tree.
How would your approach change if there were infinitely many subtrees to process?
If the number of threads available to process subtrees is limited, how would you optimize the computation?

“Seemed manageable at first.”

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Snowflake·Software Engineer·Technical Phone Screen

Jun 2026

Snowflake software engineer interview, second round. One algorithmic problem involving arrays and distance calculations. Not much else to go on from what I remember.

You're given an array of 0s, 1s, and 2s. For each element that is a 1, find the distance to the nearest 2 in the array.

“My first instinct was BFS and I think that's the right call, treat every 2 as a source and expand outward.”

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Snowflake·Software Engineer·Technical Phone Screen

Jun 2026

Snowflake's technical screening for a software engineer role is done through an AI voice interviewer called Chakra. It's async and take-home, so you do it on your own schedule. Covers your background, some applied scenarios, and collaboration stuff, then flips it around so you can ask questions too.

Walk me through your experience and background relevant to this role.
Describe how you'd approach a technical scenario relevant to the software engineer role.
Tell me about a time you had to collaborate across teams or make a decision with incomplete information.
Do you have any questions for us?

“Pretty standard opener but talking to an AI voice bot makes it feel weird.”

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Snowflake·Software Engineer·Technical Phone Screen

Jun 2026

Snowflake SWE interview with a grid traversal problem that sounds deceptively simple but has a clean optimal solution most people probably overthink.

Given a 2D grid containing desk cells, bathroom cells, open walkable space, and walls, find the shortest path distance from every desk to its nearest bathroom using 4-directional movement.

“My first instinct was to BFS from each desk separately, which would have been a mess at scale.”

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