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Netflix interview notes, page 7 of 20

FAANG / Big Tech

Most of these Netflix write-ups come from Software Engineers (136), then Data Scientists (23) and Product Managers (16). The most reported rounds are the technical phone screen (94), the system design round (48), the product sense round (14) and the behavioral / leadership round (11).

191 interview notes · updated Jul 2026

Netflix·Software Engineer·Technical Phone Screen

May 2026
Netflix SWE interview with a matrix simulation problem. Nothing too wild but the gravity mechanic adds a layer that trips you up if you jump straight to the rotation.
  • You're given an m x n grid where each cell is a stone, an obstacle, or empty space. Apply gravity so stones fall and settle, then rotate the entire grid 90 degrees clockwise. Return the resulting matrix.

“I went for the rotation first, which was a mistake.”

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Netflix·Data Scientist·Technical Phone Screen

May 2026
Netflix data science interview with a fairly meaty stats/experimentation question. Single question but it had multiple layers, so expect to spend a while on it. The setup was clean but the covariate discussion at the end is where things got interesting.
  • You have a user-level randomized experiment comparing personalization vs. no personalization, with minutes streamed as the outcome. How would you estimate the average treatment effect, report a 95% confidence interval, and decide whether to use the available pre-treatment covariates?

“Three parts and the first two felt fine.”

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Netflix·Software Engineer·Technical Phone Screen

May 2026
Netflix coding screen, one algorithmic problem, pretty standard sliding window stuff but the details matter more than you'd think.
  • Given a list of strings (or any sequence), find the length of the longest contiguous sublist with no repeated elements.

“Classic sliding window.”

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Netflix·Software Engineer·Technical Phone Screen

May 2026
Netflix coding interview where they had me solve a tree depth problem and write my own test cases on the spot. Not the hardest problem but the test case part tripped me up more than I expected.
  • Implement a solution to compute the maximum depth of a binary tree, then write your own test cases covering edge cases like an empty tree, a single node, a skewed tree, and a balanced tree.

“The actual algorithm wasn't the hard part, I had that in a few minutes.”

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Netflix·Software Engineer·Technical Phone Screen

May 2026
Netflix coding round for a software engineer role. One DFS problem with a long, complicated prompt and 45 minutes to get through it. Tight.
  • Given a tree, print the level of each node and determine whether each node is 'balanced' according to the problem's definition.

“The prompt was way longer than expected and took a few minutes just to parse what they were actually asking.”

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Netflix·Software Engineer·Onsite - Coding / Algorithms

May 2026
Netflix SWE coding round. The problem looked familiar on the surface but had a twist I wasn't ready for, and it showed.
  • Implement a topological sort variant where you must also track a DP-style constraint that activates once all prerequisites for a node are satisfied.

“I'd seen topological sort problems before and thought I had it.”

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Netflix·Software Engineer·Onsite - System Design / Architecture

May 2026
Netflix system design round for a software engineer role. The main problem was building a key-value cache with per-key TTL, and the conversation went pretty deep into eviction, concurrency, and scaling. Left feeling okay about it but not great.
  • Design a key-value cache that supports setting a value with a per-key TTL, retrieving a value only if it hasn't expired, and deleting a key. Walk through your eviction strategy, thread-safety considerations, and how this scales.

“Started with the basics: a hashmap storing value plus expiry timestamp, check on get and return null if stale.”

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Netflix·Software Engineer·Onsite - System Design / Architecture

May 2026
Netflix system design round, one question about distributed systems theory and how I'd actually applied it in practice. Pretty focused interview, no fluff.
  • Walk me through a project where you had to apply the CAP theorem and explain the trade-offs you made.

“This is the kind of question that sounds easy if you know the theory but they really want a real project, not a textbook answer.”

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Netflix·Software Engineer·Technical Phone Screen

May 2026
Netflix coding screen, one problem, pretty focused on efficiency constraints from the start. Not a lot of back-and-forth, just solve it and explain your reasoning.
  • Given an array representing a sequence of shows watched, find the length of the longest streak where the same show appears consecutively. Must run in O(n) time with O(1) extra space.

“The O(1) space constraint is what tripped me up at first.”

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Netflix·Software Engineer·Technical Phone Screen

May 2026
Netflix SWE interview with a custom data structure problem that had more moving parts than I expected. The weight-based eviction twist is what got me.
  • Design and implement a cache that supports get(key) and put(key, value, weight) operations, where the cache has a total weight capacity. When adding a new entry would push the total weight over the limit, evict the entry with the highest weight. Target O(log N) time for both operations and explain your data structure choices.

“I went straight for a HashMap plus a TreeMap keyed by weight, which felt right.”

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