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Snowflake interview notes, page 5 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·Frontend Engineer·Technical Phone Screen

May 2026
Frontend coding round at Snowflake where they had me implement an EventEmitter class from scratch. Pretty classic question but there are enough edge cases to trip you up if you haven't thought it through carefully.
  • Implement an EventEmitter class with on, off, emit, and once methods supporting a standard pub/sub interface.

“The basic structure came to me quickly.”

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Snowflake·Software Engineer·Onsite - System Design / Architecture

May 2026
Snowflake system design round, one big open-ended distributed systems question that basically asked you to design everything from scratch. Felt like a gauntlet more than an interview.
  • You're given a vague distributed systems prompt. Walk through how you'd clarify requirements, define use cases and SLAs, design external APIs, pick a data model and sharding/replication strategy, justify your consistency model, explain read/write paths, handle failures, leader election, backpressure, hot keys, caching, schema evolution, observability, security, and capacity planning. Then present your architecture and defend the trade-offs.

“This question is basically asking you to do a full systems design course in 45 minutes.”

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Snowflake·Software Engineer·Technical Phone Screen

May 2026
Snowflake SWE interview with a greedy optimization problem that looks straightforward but has a few wrinkles worth thinking through carefully.
  • You manage a virtual data warehouse with n query types, each with a fixed runtime and a per-run revenue. You have K total minutes and must pick exactly one query type to run repeatedly. How do you maximize total revenue, and which query type do you choose?

“My first instinct was to sort by revenue and just pick the highest one, which is wrong.”

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Snowflake·Software Engineer·Technical Phone Screen

May 2026
Snowflake software engineer interview with a tree manipulation problem that looked clean on paper but had a few moving parts worth thinking through carefully. The coding round felt like a mid-level systems-adjacent question dressed up as pure algorithms.
  • You have two structurally identical complete binary trees T1 and T2. Modify T2 so that each node in T2 holds the sum of all values in the corresponding subtree of T1. Implement this in O(n) time and explain your space complexity and traversal strategy.
  • Implement a buildCompleteTree function that takes a level-order integer array and constructs a complete binary tree from it.

“My first instinct was to do a preorder traversal but then I realized I needed the subtree sums, which means you actually want to compute bottom-up, so postorder made more sense.”

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Snowflake·Software Engineer·Technical Phone Screen

May 2026
Snowflake coding round, one tree problem the whole time. Pretty focused session, nothing crazy on the surface but the edge cases sneak up on you.
  • Given a tree with a target node X, return the height of the tree after removing X and its entire subtree. Height is defined as the number of edges on the longest root-to-leaf path.

“I jumped straight to DFS and felt pretty good about it, but then realized mid-explanation I wasn't handling the case where X is the root cleanly.”

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Snowflake·Software Engineer·Technical Phone Screen

May 2026
Snowflake software engineer interview with a graph traversal problem that also required building a small simulator on top of the core solution. Pretty standard algorithmic round but the added simulator layer made it feel more applied than usual.
  • Given a network of wiki pages where each page links to other pages, find the minimum number of clicks to navigate from a start page to a target page. You also need to implement a simulator that, given a page, returns all the links on it.

“BFS was the right call and I knew it pretty quickly.”

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Snowflake·Software Engineer·Technical Phone Screen

May 2026
Snowflake SWE interview with a tree manipulation problem that looked manageable on the surface but had some tricky edge cases once you got into the deletion logic.
  • Given the root of an N-ary tree and a set of node values to delete, implement the deletions such that each deleted node's children are promoted to take its place under its parent. The root is guaranteed not to be in the delete set. Return the maximum height of the resulting tree, where height is measured in edges.

“The promotion logic is where I got tangled.”

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Snowflake·Software Engineer·Onsite - Multi Round

May 2026
New grad candidate in Toronto going through Snowflake's full interview loop, which includes two initial coding screens followed by a final virtual onsite with coding, behavioral, and system design rounds. The post is more of a prep request than a full debrief, so details are sparse, but the coding problems mentioned give a decent sense of what to expect.
  • Implement a tax calculation function given income brackets and rates.
  • Merge two sorted linked lists.
  • A modified version of the tax calculation problem with altered constraints.
  • An additional coding problem in the screening round (non-LeetCode style).

“Came up in the early screening rounds.”

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Snowflake·Software Engineer·Technical Phone Screen

May 2026
Snowflake technical screen with a graph problem I wasn't fully prepared for. The constraint propagation angle made it trickier than a plain DAG traversal and I fumbled the conflict resolution part pretty badly.
  • You're given a DAG where each node has explicitly allowed and disallowed letter sets. Constraints propagate transitively from ancestors. For each node, compute the effective allowed and disallowed sets after full propagation, and explain how you'd handle conflicts where one ancestor allows a letter that another ancestor disallows. What's the time complexity?

“I got the basic traversal down fast enough, topological sort and merge sets as you go.”

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Snowflake·Software Engineer·Technical Phone Screen

May 2026
Snowflake software engineer interview with a classic parentheses balancing problem that escalated pretty fast into multi-bracket territory. Not a bad experience but the follow-up caught me more off guard than it should have.
  • Given a string of only '()' characters, determine whether the parentheses are balanced. Then extend your solution to handle '[]' and '{}' with correct nesting and ordering. Walk through your algorithm, the data structure you'd use, time and space complexity, and edge cases like empty strings or unexpected characters.

“Started fine with the basic version, stack-based, push on open and pop and check on close.”

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