Here, we’ll talk about the hiring process of FAANG companies. We’ll also throw in some guidelines on how to tell you’re ready for a FAANG interview.

You’re a data professional, or you want to become one. That’s clear because you wouldn’t be here otherwise. You probably came across this acronym – FAANG. You couldn’t miss it even if you tried. FAANG is a thang these days.

Why? The number of jobs they offer. Their sexiness. The more-than-adequate salary that comes with it. Prestige. Working with the most advanced technologies. Unfortunately, you must go through the hiring process if you want to get a job at one of these FAANG companies.

Knowing how their hiring process works won’t get you a job per se. But it is an essential part of job interview preparation. Without it, you’d be groping in the dark. How many interview rounds are there? Is it all coding? Is there coding at all? Which programming languages are most important? Which technical topics? Are there behavioral questions?

It’s essential you know the answers to these questions so you can structure your interview preparation and tailor it for a particular company. This ensures your practice is efficient and focused, which increases the chances of you getting a job. That’s the only reason why you’re here, isn’t it?

Let’s start from the basics and see what FAANG means. No, it’s not F****** Analysts Are No Good.

What Are the FAANG Companies?

FAANG are the Big Tech – the five largest US tech companies. These are Facebook, Amazon, Apple, Netflix, and Google. OK, The Artist Formerly Known As Facebook is now called Meta. So maybe the new acronym should be MAANG? MANGA? We’ll leave that for others to decide.

FAANG represents the leaders in their respective technologies, so it’s no coincidence they are also among the most valuable public companies.

Why Is Microsoft Not a Part of FAANG?

We mentioned earlier that FAANG represents the largest companies, but that’s a lie. Netflix is an intruder here. Or at least, it became recently. When the acronym was initially coined, Netflix really was among the five biggest companies.

However, its valuation has dropped in recent years, so there are suggestions to replace Netflix with Microsoft.

But, even though FAANG tried to put together the five largest companies, it seems size was never the only criterion. Nor the stock valuation since Facebook/Meta is outside the top 20 stocks.

Even more important appears to be companies’ significance on social change, and that’s why Netflix and Facebook/Meta still stay FAANG members.

And what about Microsoft? It is an undisputed leader in desktop operating systems and office productivity software. There are also several other technologies where Microsoft is dominant or is among the top companies. However, it seems it doesn’t satisfy the criteria for driving major social change.

Maybe it will be included in the future, but for now, it’s five companies, and it’s FAANG.

How FAANG Companies Hire Data Pros

Even though the hiring processes can be similar between FAANG companies, we’ll check every company to make sure that we cover all similarities but also, more importantly, differences.

That way, you can create a general approach for all five FAANG companies and then tweak it for each company individually.

Facebook/Meta

A general overview of the process is given on the official Facebook website:

1. Applying for a job
2. Recruiter interview
3. Phone or video interview
4. Onsite interviews

Let’s go through each step and see what you can expect.

1. Applying for a Job

There’s this old joke about a man who, for years, prayed to God for a lottery jackpot. One day God got fed up and said to the man: “OK, you’ll get the jackpot, just stop bothering me!” The man was happy, and God was happy, too. After some time, God again started getting prayers from the same man. He angrily asked him: ”What do you want now!?”. The man answered: ”You promised me the jackpot, but after years and years, I still didn’t get it.” The God rolled his eyes and said: ”Buy the bloody lottery ticket first!”

Don’t be that guy! Apply for the job. This is how the hiring process starts, be it you do it directly or you send the resume after the recruiters contact you.

You can find all open positions on the Facebook jobs page.

2. Recruiter Interview

In this stage, a Facebook recruiter will contact you and schedule a ~30 minutes call.

The purpose of this call is for the recruiter to tell you more about the job you applied for, what you can expect from this job, and working at Facebook in general.

The recruiter will also want to know more about you to get a general idea of your suitability. Reading a resume is one thing, but talking to the person behind it makes a picture more complete. Usually, you’ll have to talk about your education and experience you mentioned on the resume, your expectations, and your motivation for the job and working at Facebook.

Sometimes, there will be some very general technical questions to screen your technical proficiency. Putting it more bluntly, to check if you lied in your resume.

3. Phone or Video Interview

This stage will take about 45 minutes of your time. Depending on the job, the interview can be via phone or video link. This time you’ll talk with the hiring manager or your potential team member.

You will again walk the interviewer through your resume, but only shortly. The focus of this interview will be your technical skills. That’s why you’re interviewing with the hiring manager or a team member: they want to screen your technical suitability for the job.

You’ll usually have to answer several technical questions specific to the position you’re interviewing for. If it’s a video interview, and it usually is for data pros, expect one or two coding questions. Again, which language will be tested depends on the job specifics.

4. Onsite Interviews

This is the last stage in which you can do anything about your hiring. Imagine it like a final fight with the main boss. Except, there are several main bosses, so to speak. And they all want to find your weaknesses.

The onsite interviews take place in person at Facebook premises. Sometimes, despite the name, they can be video interviews. This takes virtually the whole day, with three to six interviews, around one hour each.

If it’s a real onsite interview, expect to have lunch with your interviewer or all of them. Yay! This is to talk more casually about your suitability for the role and being a team member.

The onsite interviews include everything. Expect to get several coding questions. The non-coding questions will still be mostly technical. Of course, there will also be behavioral questions, where you’ll talk about your experience, teamwork, and problem-solving. The goal is to assess, aside from your technical competence, whether you’re a good fit for the team and the company as a person and a professional.

The interviewers are usually your superior(s), teammate(s), and other colleague(s).

Amazon

Amazon, or AWS, to be more precise, is also very informative about its hiring process. This process can be divided into five general stages:

1. Online application
2. Assessments
3. Phone Interviews
4. In-person interviews

1. Online Application

You should go to the AWS jobs page, where you can search for jobs by role. When you open the role, there’s its short description, the number of open jobs, and a link to each job by the team there. Once you pick your role, you’ll have to open a profile to apply, and then you’ll be guided through the job application.

2. Assessments

The assessments are done online and are time-limited. You can be required to take it during the application process, or you’ll get it from Amazon after you send your application.

The main point of this stage is to assess your working style and how it fits in a team and Amazon as a whole. The questions will revolve around Amazon's Leadership Principles.

While the number and type of assessments depend on the job, there are two distinct types.

One is a work style assessment, which takes up to 20 minutes to complete. The focus here will be to check your suitability for Amazon’s work culture. For example, to see if you prosper when work is clearly structured or if you thrive in a more chaotic environment.

The other assessment type is a work sample simulation. It’s a bit longer, and it takes up to 60 minutes. It will put virtual tasks in front of you. Your goal is to tackle these tasks the way it adheres to the Leadership Principles. It boils down to how you resolve issues with colleagues, answer the client’s questions, solve problems, handle multiple tasks, and communicate.

Of course, for most data pros, this will also include several coding questions of medium to hard difficulty, which will also include explaining your approach and solution.

3. Phone Interview

There will usually be one to two phone interviews with a recruiter and/or a potential colleague. For data pros, this will be a combination of coding and behavioral questions. You’ll probably get one or two coding questions just to check you generally have the required knowledge.But generally, the interviews will revolve around behavioral questions. The interviewers will try to examine your experience, handling situations and problems at previous jobs, how you approach challenges, etc.

When answering the questions, Amazon prefers the STAR format.

4. In-person Interviews

The in-person interviews are, actually, not in-person at all. At least not in the old-school meaning. Amazon is still cautious about the COVID-19 pandemic, so all in-person interviews are done online via Amazon Chime.

There are usually up to seven interviews that will test your stamina, among other things. Each interview will be up to one hour, so you’ll be interviewing the whole day. And no free lunch at the premises!

As usually is the case, you will be interviewed by a whole range of people: your colleagues, superiors, and other team members.

What is typical for Amazon is that one interview will be by bar raisers. The bar raisers are neutral third parties that provide objectivity and focus on the company's long-term strategy, assessing how you fit in that strategy. The bar raisers get the name from their purpose of raising the bar at Amazon and hiring people better than the average Amazon employee.

The in-person interviews will consist of coding and non-coding technical, domain, and behavioral questions. Amazon also assures you they stopped using brain teasers, so you’re safe from this type of question.

Apple

Apple, like all other FAANG companies, is very thorough in its search for the best candidates. Maybe even more so because it’s considered the toughest Silicon Valley employer to get a job at.

Here’s what recruiting process looks like at Apple:

1. Applying for a job
2. Phone interview
3. Online interview
4. Take-home assignment
5. Onsite interviews
6. Deliberation
7. Feedback/job offer

1. Applying For a Job

Even Apple couldn’t make this stage special. They missed their train by not referring to it as a ‘Job Applecation’.

You will either get contacted by a recruiter, or you’ll have to apply for a job via the Apple careers page. You’ll see several segments of Apple's business there. Each segment is described in detail, including each team within it.

Under each team description, there’s a link to available roles. Hopefully, you find more than one suitable enough.

2. Phone Interview

There will be one or two phone interviews: with the recruiter, a team leader, or both of them separately. These are not long calls, as they usually don’t take up more than 30 minutes.

Their purpose is to get a general overview of how you fit in the role, team, and company. You’ll talk about your experience, why you applied, your expectations from your potential employment, etc.

This stage usually doesn’t include any technical questions.

3. Online Interview

This is almost purely a technical assessment. Yes, you will probably shortly talk about your resume. But the major part of the online technical questions, which will usually include the coding questions, too.

Usually, there’s one online interview, but sometimes there’s a follow-up interview. No matter the number, the goal is to evaluate your technical proficiency.

And this is done pretty fast, as the interviews are usually only 30 minutes long.

4. Take-Home Assignment

This depends on the position you’re interviewing for, but data pros usually get a take-home assignment to solve.

It will, again, be a technical task or more of them that you need to solve and send back within a set time frame. Solving one such problem can take up to several hours. Don’t be scared; it is supposed to take some time and be hard.

Which assignment you get depends on the job you applied for, as the problems are tailored to test specific skills for a particular position.

5. Onsite Interviews

The onsite interviewing is the most dreaded part that can sometimes feel like onsite roasting. But try not to worry too much about that. If you got to this stage, then you’re for sure a good candidate, one of the selected few.

As with other FAANG companies, schedule this as a whole-day event in your calendar. You’ll get to Apple premises and be interviewed by eight to 15 people, sometimes one-on-one and sometimes one-on-two. In total, it will take around six hours to go through everything.

Luckily, this will include lunch. Relax, but don’t relax too much because you’ll be interviewed (a little more lightly, admittedly) even as you cut your steak or tofu, whichever is your preference.

The onsite interviews will try to screen you from head to toe, similarly to in other big companies. You’ll be asked coding and non-coding technical questions, behavioral questions, and questions testing your domain knowledge.

Netflix

The way Apple is famous for having the most trying hiring process, Netflix is famous for its focus on its culture. It’s not to say that other companies are not, but Netflix is even more: reportedly, 40-50% of the Netflix hiring process is focused on culture fit.

Regarding the process itself, here’s what you’ll have to go through:

1. Applying for a job
2. Recruiter phone interview
3. Hiring manager interview
4. Onsite interviews

1. Applying for a Job

Netflix, too, has a career page where you can search for jobs by keyword. After that, the list of jobs opens up, and you can filter them by team and location.

You can get information about each team here, linking you to open positions and related teams.

Hope you find something that interests you quicker than you do when browsing movies on Netflix.

2. Recruiter Phone Interview

If your resume gets selected, the recruiter will contact you to arrange a phone interview. As we mentioned, approximately half the time you’re being interviewed will be to screen your cultural fit.

Because of that, the recruiter will send you Netflix Culture Values, so you can’t say you weren’t informed about what they’re looking for.

This first interview itself will be short, around 30 minutes. Its purpose is for the recruiter and yourself to introduce each other. The recruiter will talk about the company and the position. And you will have to talk about your experience, answer some behavioral questions, and make sure you strike a chord with your motivation for applying and wanting to work at Netflix.

The usual stuff.

3. Hiring Manager Phone Interview

Now, you’re ready to interview with a hiring manager. Unlike in other companies, hiring managers at Netflix are usually in charge of conducting the interviews and, hence their title, hiring.

As usual, the interview will have a short introductory stage where you’ll talk about yourself and answer few behavioral questions, again to check your cultural fit.

However, the focus of this interview is technical skills. So be ready for up to an hour of technical and coding questions.

Sometimes there’ll be a possibility to opt for a take-home assignment instead of the technical interview. Both are equally valued, so it’s only up to you and in which situation you feel most comfortable.

Regarding take-home assignments, they usually don’t take up more than eight hours.

4. Onsite Interviews

As with other companies, this will be a whole-day experience. The day will be split into two parts.

Part 1 will include four-five interviews and will be focused almost entirely on coding. Some questions can also be in a form that doesn’t require writing code but does require other technical skills. Everything depends on the position you’re interviewing for.

These interviews will be one-on-one, sometimes one-on-two, with hiring managers and technical staff.

Unlike Amazon, Netflix occasionally does ask you to solve a brain teaser.

The last interview of the first part will be with HR. There, you’ll once again have to prove that you fit into Netflix's values.

Each interview will last around 45 minutes.

If you do well in the first part, you’re going to Part 2. This part includes two-three interviews with HR, the hiring manager, and another manager within a technical domain. Again 45 minutes per interview, but this will be more relaxed.

You passed your technical and coding tests. Even though your technical skills will again be evaluated here, the focus will be on fitting into the Netflix culture. This is what we mentioned in the beginning, and that’s why the recruiter sent you Netflix Culture Values in the first place. They really care about that! From the hiring processes of other FAANG companies, we didn’t see that much focus on culture. However, for Netflix, it seems equally important as technical skills. Some are reporting that, for Netflix, your personality is even more important than your technical skills.

Google

We’ve come to the last FAANG company in our coverage – Google. They try to make your life easier by describing their hiring process in quite detail. But don’t be fooled by transparency; getting a job at Google is not an easy task.

The first step that will make this easier is knowing how Google hires.

1. Applying for a job
2. Online assessment
3. Online/phone interviews
4. Take-home assignment
5. Onsite interviews

1. Applying for a job

Google has a great job search page. You can find all open positions there. Additionally, you can filter jobs by location, skills and qualifications, education level, job type, and organization.

When you click on ‘Apply’, you’ll be guided through the application process.

2. Online Assessment

Once your resume gets reviewed, and you are selected for the next stage, you’ll be contacted to arrange a time slot for online assessment.

For data professionals, this includes a coding quiz, almost without exception. Depending on the position, you can be expected to take some other aptitude tests, such as numerical reasoning or situational judgment tests or the personality survey.

3. Online/Phone Interviews

After passing the online assessment, you’ll then have one or two online or phone interviews.

These will be interviews lasting up to one hour each. They are usually with a recruiter and hiring manager or a team member.

As with other FAANG companies, this hiring stage’s purpose is to gauge how fit you are for the position in terms of experience, personality, and technical skills.

4. Take-Home Assignment

Whether you get this depends on the job you applied for. Depending on this also changes the task you need to solve. For data professionals, it’s usually some project or a case study that involves coding. These are designed not only to see your coding skills but also to test your problem-solving skills and how you approach a broader problem than just simply querying databases and calculating some metrics.

5. Onsite Interviews

As with other FAANG companies, this is the most stressful part of the hiring process. It’s a whole-day event where you’ll typically go through two to six interviews, each lasting around 45 minutes, sometimes even more. The interviews can be onsite but also online.

This is the last stage, so you can expect a thorough examination of how you fit into a role, team, and company.

For data pros, your technical skills will be even more in the spotlight – you’ll be coding and answering technical questions a lot.

Due to the variety of skills and attributes tested, you’ll get interviewed by a range of people, such as the hiring manager, team members, members of other teams you’ll work with, etc.

How Do You Know if You’re Ready to Interview at FAANG?

Short answer – you don’t.

The long answer is that you really can never be 100% sure. The only way would be to get all the questions and desired answers in advance, but this won’t happen, will it?

However, there are some ways to ensure you can be reasonably confident in doing good in the FAANG hiring process. Remember, the competition is fierce. For example, in 2020, Google had only a 0.67% acceptance rate! If you don’t get a job, it doesn’t mean you’re a no-good data professional.

Getting a job at FAANG requires long-term preparation, as there are some requirements you can’t acquire overnight. Over lots of sleepless nights, more probably.

Here are some steps we recommend you take before you claim you’re ready for a FAANG interview.

Read the job description well. If you’re interested in certain positions at FAANG, read the requirements well and make sure you really satisfy the criteria regarding experience, technical skills, and tools used. If you do, and try to be as objective as possible, then apply.

If you don’t, then you need to go to the next step.

Get working experience and skills. Having years of experience takes, well, years. Stay at your job and try to get as much experience as is required by your desired jobs at any FAANG company. Also, pay attention to the skills that are required. It would be great if your job would teach you those skills. If not, try to change jobs within a company. Or try to learn those skills on your own, with plenty of online (and maybe your local) sources.

Another option is to change jobs if you’re really determined to work at FAANG at some point in your career.

Once you have the experience and skills and you apply for a job comes the interview preparation. Start it even before you get invited to an interview. The preparation should start with thoroughly researching the company, which includes its history, market, products, competitors, financial standing, organizational structure, and so on.

You should also read the job description through and through, so you can talk about it in the interview. You should even research the interviewers when that’s possible.

As a data professional, your interview preparation must focus on technical skills. A job description will be your starting point for knowing which programming languages and tools are required to know. If you feel rusty, take online courses or coding challenges to improve your skills. Additionally, you should research which questions are asked in the interviews. After that, make sure that you solve as many as possible actual interview questions or other challenges that focus on the most tested concepts.

Depending on the position, make sure that you solve some other technical questions. For example, statistics, modeling, data structures, system design, and even product questions. If the company you’re interviewing for gives take-home assignments, try to solve some of these, too.

Preparation is not only for technical questions. You should also prepare for the domain and behavioral questions. The domain knowledge will usually stem from your working experience. But it won’t hurt to learn something that is company or industry-specific.

The behavioral questions require another type of preparation. We don’t recommend having answers ready in advance and learning them by heart. What you should do is, again, find the questions that come up often and think about the major bullet points you want to mention in your answer.

For example, if the question asks you to talk about your least successful project, it won’t be good trying to remember which one was that in the interview. You should have outlined in your head the main dots, such as which project was that, why it was unsuccessful, and what you learned from it. And the interview, the only thing you need to do is connect those dots.

Try to strike a balance between robotic mouthing of words and a complete, free jazz level of improvisation.

Get interview experience. You can practice all you want, but nothing beats an actual interview. The more interviews you go through, the more you’ll be ready for FAANG interviews. Other data science companies have thorough hiring process and technical interviews. After several interviews, you’ll better know what you can expect.

With each interview, there will be fewer surprises and more familiarity with all the technical question variations, trick questions, behavioral questions, and so on. With every ‘failed’ interview, you will hopefully reflect on what you think went wrong and why. If you get feedback from the interviewer, use that too to improve for your next interview.

This experience will mean a lot when it comes to interviewing at FAANG. And failing at FAANG interviews is also highly recommended! It’s relatively rare that people get a job at FAANG on the first attempt. Usually, it takes several tries, even at the same company.

If you get a job immediately, fair play to you! But if you don’t, use this as an opportunity to learn and try again!

Which FAANG Company Pays the Most to Data Pros?

We’ve been talking a lot about the hiring process and preparation. It all takes a lot of time, planning, and willingness to make it there.

Thousands, even millions, are ready to go through the process. We can talk about technology, culture, team, challenges, and everything in between. But one of the most important factors that draw people is salary.

FAANG companies are famous for high pay, but which pays the most? Data scientist, machine learning engineer, and data engineer are among the most popular data jobs, according to Glassdoor.

We used FAANG companies data for those three jobs to see which company pays the most.

Below is the annual median total salary (including additional salary) for each FAANG company.

If you’re a machine learning engineer or a data scientist, you could earn the most at Facebook and Google, with salaries between $212,000 and $225,000.

At Netflix, the data engineers have the highest salary at Netflix; $208,882. Netflix also comes third for machine learning engineer salaries.

Apple is third in data science salaries. But machine learning and data engineers will receive less than at Netflix.

Generally, Amazon pays the least across all data positions.

For further reading, refer to our data science salary article, where we detail this position.

Summary

This article explained the hiring process in every FAANG company. As you can see, the process is somewhat similar in general, but each FAANG company has at least one quirkiness that makes it different from others.

As a data pro, you’ll primarily have to tackle a lot of coding and non-coding technical questions. These could go in different directions depending on the position you’re interviewing for. Some examples are system design, statistics, business cases, products, algorithms, data structures, or some other technical questions.

StrataScratch can help you prepare most of these questions. We have numerous actual interview questions from FAANG companies, both coding, and non-coding. We have already solved many of these questions and showed you how to do it in our interview guides. You can find them all on our blog.