Notion

Mid-sized

Most of these Notion write-ups come from Software Engineers (25), then Data Scientists (2) and Product Managers (2). The most reported rounds are the technical phone screen (21), the hiring manager screen (2), the take-home assignment (2) and the cross-functional panel (1).

29 interview notes · updated Jul 2026

Notion·Software Engineer·Technical Phone Screen

Jul 2026

Notion SWE interview with a coding problem centered on building a text document class with undo/redo support. The skeleton was provided upfront which was nice, but the real pressure came from the follow-up discussion about data structures and complexity.

Implement a TextDocument class in Python that supports inserting characters at the end, deleting characters from the end, and undo/redo functionality. A skeleton with the class structure is provided. After any new operation is applied, the redo history should be cleared. Operations should run in time proportional to the size of the change, not the full document size.

“The skeleton made it feel approachable at first but I got tripped up on the undo storage.”

View Post

Notion·Software Engineer·Hiring Manager Screen

Jul 2026

Two-part interview for a Data Engineer role at Notion: a hiring manager screen and a cross-functional partner conversation. Pretty behavioral-heavy, lots of digging into specific projects and how you work with others. Nothing too surprising but you need real stories ready.

Why do you want to join Notion specifically?
What is driving you to leave your current role?
Walk me through a project you're proud of, from how you framed the problem through to how you measured whether it worked.
Tell me about a time you worked closely with a data scientist or another cross-functional partner. How did you split the work and handle disagreements?
If you could redo that project, what would you change?
What constructive feedback have you received from your manager, and what did you do with it?

“Prepared this one but still fumbled a bit trying to sound genuine rather than rehearsed.”

View Post

Notion·Software Engineer·Technical Phone Screen

Jul 2026

Notion Data Engineer interview with a coding question that was more interesting than I expected. The problem sounds like a warmup but the complexity discussion is where they actually wanted to see your thinking.

Given a string and an integer k, write a function that counts the number of distinct substrings of length exactly k in the string. Walk through your approach, complexity, and edge cases.

“Sliding window plus a hash set, pretty mechanical to implement.”

View Post

Notion·Software Engineer·Technical Phone Screen

Jul 2026

Notion SWE interview with a frontend-heavy coding problem. Pretty focused on product thinking through code, which makes sense given what Notion actually is.

Build a Todo List that supports nested items and toggling items between done and undone states.

“The nesting part is where things get interesting and also where I spent too long overthinking the data structure.”

View Post

Notion·Software Engineer·Technical Phone Screen

Jun 2026

Notion Data Engineer interview with a coding round focused on a classic grouping problem. Nothing too wild but they did want you to think through the tradeoffs between two different approaches, not just get to a working solution.

Given an array of strings, group all the anagrams together and return the grouped lists.

“Jumped straight to sorting each string and using that as a hash map key, which works fine.”

View Post

Notion·Software Engineer·Technical Phone Screen

Jun 2026

SQL-heavy technical screen for a Data Engineer role at Notion. The main problem was a multi-part query that built on itself, and the trick was figuring out why you can't just collapse everything into one GROUP BY.

Given a multi-part SQL problem where each stage filters on the result of the previous one, how would you use boolean aggregation (like BOOL_OR) to flag groups, then chain those flags across sub-queries to arrive at a final metric? Also, why doesn't a single GROUP BY pass work here?

“This took me longer than I'd like to admit to structure properly.”

View Post

Notion·Software Engineer·Technical Phone Screen

Jun 2026

Notion data engineer interview, SQL-focused technical screen. One question but they dug into it pretty thoroughly, including schema assumptions and how you'd handle edge cases.

Given an events table, write a SQL query to find the country with the highest total number of events. If there's a tie, return all tied countries.

“I went straight for GROUP BY country, COUNT(*), ORDER BY count DESC LIMIT 1, which works fine until they asked about ties.”

View Post

Notion·Software Engineer·Technical Phone Screen

Jun 2026

SQL technical screen for a Data Engineer role at Notion. Just the one question but they went pretty deep on edge cases, which I wasn't fully ready for.

Given an events table with columns like event_id, event_type, user_id, and event_time, write a SQL query to find the event_type that occurs most frequently.

“Started with the obvious GROUP BY event_type plus a COUNT and ORDER BY count DESC with LIMIT 1, which is fine.”

View Post

Notion·Software Engineer·Technical Phone Screen

Jun 2026

SQL-heavy technical screen for a Data Engineer role at Notion. One question, but they pushed on edge cases and made sure you actually understood what was happening under the hood.

Given a blocks table and an edit_events table, write a SQL query to find the percentage of blocks that have never been edited.

“I went with a LEFT JOIN approach, grouped by block_id, counted edits per block, then wrapped it in an outer query with a CASE WHEN to flag zero-edit blocks.”

View Post

Notion·Data Scientist·Take-home Assignment

May 2026

SQL take-home for a DS role at Notion, three questions around a doc collaboration dataset. Pretty clean problem set, nothing crazy algorithmic, but the collaboration rate definition question had more nuance than I expected.

Given a table of document access events, compute the distribution of how collaborators ended up on documents, including counts and percentages.
For a given input user ID, find the other user they have collaborated with the most, where collaboration means both users appear on the same document page.
Which country has users who collaborate the most? Define a collaboration rate per country, justify your numerator and denominator, then compute it.

“Seemed straightforward until I had to decide whether to count unique users globally or unique (page, user) pairs.”

View Post

Notion interview FAQ

What rounds are in the Notion interview?

Candidates most often report a technical phone screen (21 write-ups), a hiring manager screen (2), a take-home assignment (2) and a cross-functional panel (1).

What does the Notion technical phone screen cover?

Across 21 technical phone screen write-ups, the most tagged question topics are Technical Trade-offs (19 questions), Algorithms & Data Structures (17) and Data Modeling (14).