Netflix SAE Interview Experience｜Technical + Case double exams, the pace is too fast like a boss battle.

It just ended a while ago. Netflix SAE interviews, the whole process from technical screening to superday went through a total of five rounds.
Overall feeling: medium difficulty but super fast paced, especially at the end VO five games in a row, physical and mental energy are stretched to the limit.
Here's a detailed description of each round and how I felt about it.

Round 1: Technical Screening

This round is mainly in the form of an online written test through the CodeSignal Conducted. The questions were technical in nature with a very high percentage of SQL.
While the topic is generally not difficult, the pitfall is - no data table schema is provided!
So you can only guess the fields based on the question stem, or column by column print to see which field to join, quite a test of experience.

Sample title:

Question 1.
You are given two tables. users And subscriptions. Write a query to find the number of users who have at least two overlapping subscription periods.

Return user_id and count of overlapping periods.

Note: Two periods overlap if their start and end dates intersect.

The key to this question is self-joining, to determine whether the time intervals of two subscriptions overlap. It's logically simple, but if you don't have a schema, you'll have to try to print the data format first, which is very time-consuming.

Another question is a variant of calculating the average user behavior:

Question 2.
Find the average watch time per active user per week from the viewing_activity Only include users who watched more than 5 hours in that week.

This type of question is typical, Netflix loves to test "Data Aggregation + Group Filtering + Time Window" logic. Overall feeling:

SQL difficulty is around LeetCode medium;
Not too many fancy algorithms;
The point is that the logic of the data should be clear.

Round 2: SQL + Data Structure + Business Case

The second round was more generalized, and started out as a combination of a take-home test + technical discussion.

Part 1: SQL
A medium-difficulty question that examines multi-table joins, group by, and the window function.

Question 3.
Given tables shows, episodes, and ratings, write a query to find the top 3 shows with the highest average episode rating in the last 90 days.

The point is:

Time filtering (WHERE date > CURRENT_DATE - INTERVAL '90 days')
join three tables
group by show_id, then sort by average score

Part 2: Data Structure
Coding questions are on the easy side, like LeetCode easy-medium difficulty.

Question 4.
Given an array of integers, return True if the array can be split into two subarrays with equal sum.

Netflix rarely asks complex algorithmic questions, but rather tests you on logic, naming conventions, and boundary considerations.

Part 3: Business Case
This was my favorite part of the interview. The interviewer gave a very life-like scenario:

Case.
Netflix noticed a drop in engagement in one of its regional markets. How would you investigate the cause using data?

It's not the final answer they want to hear, it's your 'analytical framework'.
That's what I said at the time:

Step 1: Identify the problem (how much the Engagement metrics are down, what is the definition)
Step 2: Deconstruct dimensions (region, content type, device, plan)
Step 3: Examine assumptions (content quality, price changes, user distribution)
Step 4: Design validation (experiment or cohort analysis)

The interviewer kept nodding, indicating that this round was more about logical thinking.

Third round: Hiring Manager interview

This round was on the lighter side of the behavioral + fit session and the interviewer was the direct supervisor.
The chat is mostly about work experience and business understanding, for example:

What A/B experiments have you led? How do you define success metrics?
What do you do when the business side disagrees with the results of an experiment?
What trade-offs have you encountered in past analyses?

Netflix managers value communication, and especially like to hear how you "influence non-technical stakeholders".
I had a good vibe this round, more like a two-way exchange.

Final Round: Virtual Onsite (Superday)

Highlights!
There were 5 interviews in total, each lasting 45 minutes, almost back-to-back, with less than 10 minutes of breaks in between.
The pace is so fast that it's like playing five ranked games in a row.

Side 1: Cross-Functional (Sales Team)

The main test is whether you can communicate across teams.
Example title:

"How would you communicate an A/B test result that shows negative impact on sales?"

Here you are asked whether you can "translate data into business language".
They will follow-up: "What if Sales doesn't accept your results?"
The core is in the attitude and communication strategy.

Side 2: Leadership (Director Level)

It's all behavioral, for example:

"Tell me about a time when you had to make a decision with incomplete data."
"How do you prioritize analysis requests when resources are limited?"

Netflix is big on Freedom & Responsibility, and this round is all about how well you match the company's philosophy.

Sides 3 and 4: Analytics Deep Dive

These two rounds are purely case-faced and are on the difficult side, but can be prepared for.

Case Example 1.
Design an experiment to test if a new recommendation algorithm improves engagement.

What's your hypothesis?

How do you define the success metric?

How do you handle sample size and bias?

Case Example 2.
Given an A/B test result with p-value = 0.07, what would you do next?

This part is typical of experimental analytical thinking. The interviewer wants to see if you understand the business implications behind statistical significance, rather than memorizing concepts.

Side 5: HR / Culture Fit

The HR interview was just to wrap things up and it was a bit more relaxed. The main question:

Why do you want to join Netflix?
What do you think of Netflix's culture?
What is your role in teamwork?

The tone was all very kind, and we ended up talking about favorite shows (I mentioned Black Mirror and Mindhunter, and the atmosphere was great).

How to get past the Case side of a Netflix / Meta / Amazon VO?

If you're also prepping for data-heavy VOs like Netflix, Amazon, Meta.
You can try. Programhelp will provide real-time voice reminders, question structure guidance and case response optimization without interfering with the platform, so that we can help you get the dream offer steadily, just like this student.

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