Netflix There are 5 rounds of Virtual Onsite in total. The overall rhythm is very tight, and you can clearly feel that the Netflix Interview is not testing "can you do algorithms", but is repeatedly confirming whether you have already fought in this domain.
Without a practical background in advertising systems, data platforms, or large-scale systems, it can be very stressful. Today I will review the most recent Netflix VO experience I took students to participate in, including the entire process of Coding, Data Modeling, System Design, Behavioral and Domain Experience Round, and attach a high-frequency questioning template to help you understand the rhythm and key points of the interview in advance.
Netflix Interview Overview
- Interview format: Virtual Onsite
- Total rounds: 5 rounds
- Total duration: about half a day
- Technology proportion: High (Coding + Data Modeling + System Design)
- Domain weight: very high (Ads related)
Overall Netflix interview round:
- Coding (Command + Undo)
- Data Modeling (Ads Data Modeling)
- System Design (Ads Audience Targeting System)
- Manager Behavioral
- Manager/Domain Experience
To sum up this onsite in one sentence: technology is just the threshold, domain is the decisive factor.
Round 1: Coding (Command + Undo)
This round is the only relatively "normal" technical aspect. The topic is OOD type, implement one Class,support:
Execute(command)Undo(): Undo the latest command
Examine data structure design, command history maintenance, undo correctness and boundary processing
Ideas
- Use stack to save executed commands
- Each command itself must support
Execute()/Undo() - When undo pops up the latest command and rolls back
This round is not about how complicated the writing is, but about clearly expressing design ideas and ensuring state consistency for multiple executes. This round is considered the friendliest round in the entire onsite.
Round 2: Data Modeling (Ads data modeling)
From this round onwards, the difficulty level is maxed out. Including Ads-related data model design, how to store, associate, and expand advertising data, and the need to consider subsequent analysis, delivery, statistics and other usage scenarios. This interview was very uncomfortable, and it was obvious that there was not enough time at all.
While modeling, I was asked:
- Why is this field designed like this?
- How will this table be expanded in the future?
- What to do if data volume skyrockets
If you have never done Ads/recommendation/tracking related systems before, it is easy to be chased all the way to collapse.
Round 3: System Design (Ads Audience Targeting)
Design a Ads Audience Targeting System,support:
- 大规模用户数据上传
- Ad audience matching
- High concurrency and scalability for Ads scenarios
Focus on examining data ingestion (big data upload), user characteristics & audience segmentation, system scalability and fault tolerance, and trade-off in actual advertising systems. This round is not a template system design, but a strong domain driver:
- The interviewer assumes that you understand the logic of advertising placement
- Will constantly pull you into the "real business system"
If you have only prepared general system design (such as URL shortener, chat system), it will obviously not be enough.
Round 4 & 5: Manager Behavioral + Domain Experience
The previous round was regular manager behavioral, focusing on project decision-making, conflict handling, influence, and ownership.
The last round is the highlight and the most torturous round. So called Domain Experience Round, almost the entire process revolves around:
- Have you actually done anything like Ads/Data/Platform?
- Your true role in the system
- Judgment and choice when facing complex business
Instead of asking “What do you think?”, I asked repeatedly. During the interview, I was really embarrassed when I was asked:
- What exactly did you do at that time?
- Why did you choose this
- What would you change if it happened again?
Summarize feelings
Netflix’s onsite is very clear:Algorithms are not the point,Domain depth is the core of screening
Especially the Ads direction:
- Data modeling
- Ads system design
- Domain experience
If your background and job direction are highly matched, the conversation will be very in-depth; but if you are just "strong in technical ability but weak in domain", the experience will be very difficult. It’s a true reflection of Netflix’s expectations for advanced engineering capabilities.
Escort your entire interview with a major factory
When preparing for the Netflix Interview or other OA/Onsite interviews with major North American companies, if you are easily stuck in the Domain Experience, System Design or data modeling sessions, targeted guidance and practical exercises are very important.
We provide full interview and written test support, including:
- OA ghostwriting & written test assistance for major manufacturers: Support HackerRank, Niuke.com, Codesignal and other platforms to ensure 100% pass of test cases and remote traceless operation is safe and reliable.
- Interview Assistance & VO Assistance: Real-time prompts for ideas and question-answering techniques, and manual support from North American CS experts to help you stand out in interviews.
- Agent Interview / SDE & FAANG Interview: Transfer the camera and voice changing technology, and simulate the test in advance to ensure the smooth completion of the interview and direct offer.
- Full process support: From OA to technical aspects, to contract negotiation, a small deposit is paid in advance, and the balance is paid after the offer is made.
Also, it also provides customized services such as mock interviews, interview experience sharing, programming ghostwriting, resume packaging, algorithm coaching, and Quant interview assistance, making every preparation efficient and safe.Contact us, Direct Offer to major manufacturers.
