Snowflake interview notes, page 14 of 14

Large Enterprises

Most of these Snowflake write-ups come from Software Engineers (118), then Data Scientists (12) and Backend Engineers (2). The most reported rounds are the technical phone screen (91), the system design round (30), the behavioral / leadership round (5) and the online assessment (2).

135 interview notes · updated Oct 2026

Snowflake·Software Engineer·Technical Phone Screen

Jul 2026

Snowflake SWE interview that was basically three connected problems about error detection and failure propagation. The sub-problem structure felt clever at first but by part C I was running on fumes.

You have a chronologically ordered log array where each line starts with '[Info]', '[Warn]', or '[Error]'. Once an '[Error]' appears, all subsequent lines are also errors, and there's at least one '[Warn]' right before the first error. Find the index of the first '[Error]' using as few reads as possible. What do you return if no error exists?
Given a directed service dependency graph where an edge U to V means U calls V, and given the ID of the first failing service, find all services that will eventually fail due to cascading upstream failures.
Using the same graph and initial failing service, find one of the longest possible chains of cascading failures starting from that service. State your assumptions about cycles and justify them.

“Binary search, obviously, but I fumbled explaining why the guarantees matter.”

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Snowflake·Software Engineer·Onsite - Behavioral / Leadership

Jul 2026

Behavioral round at Snowflake for a software engineer role covering three classic prompts back to back: proudest project, a conflict, and a failure. The interviewer wanted specific first-person stories with real decisions and numbers, not team narratives.

Tell me about the project you're most proud of. What was your specific role, what was the hardest problem you personally solved, and what was the measurable impact?
Describe a significant disagreement you had with a coworker, another team, or a manager. How did you handle it and what came of it?
Tell me about a time you failed. What happened, what was your role in it, and what did you actually change afterward?
Looking across all three stories you shared, what pattern do you see in the kind of work and environment where you do your best?

“I overthought which project to pick and landed on something technically impressive but where my individual contribution was honestly a bit blurry.”

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Snowflake·Data Scientist·Onsite - Coding / Algorithms

Jul 2026

Snowflake Data Scientist interview that went deep into algorithmic problem solving, way deeper than I expected for a DS role. The whole session was essentially a multi-part coding and system design marathon centered on a single problem with escalating constraints. Left feeling like I'd been wrung out.

Implement an O(n^2) solution to find all unique triplets in an array that sum to zero, using sorting and two pointers. Prove your duplicate-skipping logic is correct on adversarial inputs like an array of all zeros.
Generalize the triplet sum problem to an arbitrary target T and then to k-sum for k >= 4 with pruning. What time complexity do you achieve, and how do you prevent integer overflow when summing large values?
If the array has 5 million elements and memory is capped at 512 MB, how would you approach finding all triplets using an external-memory strategy? What is the I/O complexity? And if exact enumeration is infeasible, how would you approximate the count of unique triplets using probabilistic sketches?
Given a frequency map of values rather than the raw array, compute the number of unique triplets summing to a target T in O(m^2) time where m is the number of distinct values. Handle edge cases where two or all three values in a triplet are the same.

“The basic two-pointer approach I knew cold.”

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Snowflake·Software Engineer·Onsite - System Design / Architecture

Jul 2026

Snowflake SWE interview focused on building a document storage service from scratch, starting with basic insert and search APIs, then scaling into distributed systems territory. Solid design problem that had more depth than I expected going in.

Design a document storage service with InsertDoc(filename, content) and CheckContains(filename, predicate) APIs, where the predicate supports boolean keyword expressions with && and || operators and operator precedence rules.
Extend the service with a GetAllFiles(predicate) API that returns all filenames whose documents match a given boolean keyword expression.
How would you scale this document service in a distributed environment? Describe a sharding strategy and a replication policy.

“The insert part was fine, basically just a hashmap from filename to content.”

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Snowflake·Software Engineer·Technical Phone Screen

Jul 2026

Snowflake SWE interview with two coding problems back to back. The graph one was manageable but the rate limiter problem had a tricky sliding window constraint that took me a while to reason through cleanly.

Given n courses and a list of prerequisite pairs, determine whether it's possible to complete all courses (i.e., detect if the prerequisite graph contains a cycle).
Follow-up on the course scheduling problem: if it is possible to finish all courses, what is the minimum number of semesters needed, given that you can take any number of courses per semester as long as prerequisites are satisfied?
You're given a non-decreasing array of request timestamps. A rate limiter drops a request if it exceeds 3 requests at the same timestamp, or if processing it would push the count of processed requests in any 10-second sliding window above 20. Return the timestamps of all dropped requests in order.

“Classic cycle detection in a directed graph.”

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