The ins and outs of the interview process and how you can come prepared.
If you're a data scientist, there aren’t many companies doing more than Facebook, the social networking site with over 2.7 billion active monthly users. They collect data on all of their users that data engineers help turn into valuable insights for the company. Big data is growing every year, and Facebook is one of the companies leading the charge.
On a basic level, data engineer roles include managing, optimizing, and overseeing data retrieval systems, along with building data pipelines and algorithms. As a data engineer at Facebook, you have the opportunity to build tools, infrastructure, and frameworks, that influence a variety of cutting-edge products. Data scientists help in product decisions along with software engineering, design, product management, data science, research, and more.
Facebook offers competitive pay...
The average annual salary for data engineers at Facebook is $260,000 making the job highly sought after with some fierce competition. The salary range varies widely depending on your level, with IC4s making an average of $226,000, IC5s making $325,000, and IC6s making $464,000.
Facebook also has locations across both the US and the world, with global opportunities for its employees. Of course, salary varies widely by location as well.
Because Facebook is such a large and data-driven company, there are many data science-related roles and teams to fill. Here are just a few:
Roles in this team will design and build data foundations, infrastructure, and architecture that help drive better business decisions for Facebook.
Roles in this team will design, build, and launch new ETL processes and data modeling in production, manage data warehouse plans, and collaborate cross-functionally.
Roles in this team will design and implement scalable data repositories to integrate research data, build and launch ETL processes in production, and transform user interaction data and server events data into scalable schema models.
Roles in this team will develop data processing architecture and systems for new data and ETL pipelines, and recommend improvements to existing data and ETL pipelines.
Roles in this team will build and maintain data pipelines and build models that provide intuitive analytics.
Roles in this team will work with data infrastructure, product software engineering, and product management teams to develop architecture-driven, end-to-end analytics development products, tools, and infrastructure stacks.
Facebook is known for sticking to the job requirements 100%, so if you don't meet a criterion, you will probably not be considered.
If a data engineer role at Facebook sounds like a good fit for your skillset, then here are some of their basic requirements for interviewing:
If applying online, your resume is absolutely crucial in getting you an interview, and because your recruiter looks at so many resumes, you need to do it right to get noticed.
To give yourself the best chance at getting through the resume screening, you should limit your resume to 1 page long.
👉 To learn more about formatting, read: Which resume outline should you use?
There are typically 4 sections you should include:
👉 Use this to help you determine how far back your experience should go: How far back should your resume go? Strategies for every career stage
Facebook's interview process is predictable, so if you take the time to prepare you’ll increase your chances exponentially.
The Facebook data engineer interview follows a standard interview process, in line with other Facebook technical roles:
The first step in your data engineer interview at Facebook is a 30-minute long phone interview with either a recruiter or Facebook’s HR team. In this call, the recruiter explains what to expect from the rest of the interview process, along with specifics about the data engineer role at Facebook.
This is the first technical interview that prospective employees have, and it is also a phone interview. It is time-limited to one hour, so be prepared to move quickly through questions.
The interview is conducted using Coderpad, with about eight to ten questions about SQL and Python/Java, depending on your programming language preference. The questions are divided equally between SQL and Python, and there is an algorithms question in each category.
If you make it through the first two stages, the final stage of the Facebook data engineering interview process is an onsite interview, with three full-stacked interviews (including two ETL rounds and one data modeling round), then one behavior round. A lunch break is also included.
Aside from the behavioral interview, the other interviews have a product sense element that tests a prospective employee’s product sense knowledge on key operational metrics. The questions are case-based and can require some coding.
The interview tends to be heavy on SQL, but Facebook is not necessarily examining your syntax. Your SQL will be assessed more so on DE fundamentals, for example. Your interviewer will likely be looking for you to display experience and judgment more so than asking you to solve a specific puzzle.
Facebook’s data engineer interview process assesses candidates’ abilities to utilize big data to provide actionable business insights. Their questions are standardized, especially during coding interviews.
In order to prepare for your interview, practice SQL, Python/Java, modeling, and algorithm questions including lists, arrays, dot product, JOINS, SUBQUERY, AGGREGATE functions, and GROUP BY.
Be sure to practice as if you were interviewing. After all, you will need to explain your thought process as you answer. You can practice coding on a whiteboard in order to prepare for the onsite interview.
There are websites where you can regularly practice your data science skills, including Leetcode and Interview Query. With 82 questions, Leetcode is a good place to get familiar with the types of questions you will be asked. Interview Query also gives advice on how to ace your job interview in the data science sphere.
If you are still looking to be prepared as possible, get in touch with others who have interviewed for the same position, or read about their experiences online. Glassdoor and Leetcode have discussion boards about the people’s interview experiences for Facebook’s data engineer position, as well as other data scientist positions and other positions at Facebook.
The Facebook data engineer interview consists of eight different question topics: SQL, Python, Product Case, Takehome, Algorithms, Probability, Machine Learning, and Statistics / AB testing. Facebook puts a special emphasis on skills in SQL, Python, and Algorithms.
However, you can also be asked about wide-spanning questions across the data science world, including DB performance tuning, data pipeline design, metric and visualization solution design, statistics and modeling, previous project experience, big data solutions like Spark and EMR reporting rolls like Tableau and Excel, and building data platforms or architectures.
Here are some frequently asked interview questions:
1. What's the best feature of a competing social network? Why?
2. If you had to redesign the Facebook news feed, how would you do it?
3. Let's say you were in charge of birthdays at Facebook. How would you think about this space and what new features or products would you launch?
4. How would you design a system for finding a doctor? What would you say is the goal of your solution? What makes this better than what is out there today?
It is common practice for NDAs to be signed during the onsite interview. However, the onsite interviews are based on real-world case studies, and it is important to know key operating metrics.
People generally seem to have mixed opinions about the data engineer role at Facebook, with many claiming your work will entirely revolve around SQL and you'll have a poor work-life balance.
And if moving up the ladder is your goal, many data engineers claim that you'll be working long days, making comments like "be prepared to work 80hrs a week" and be willing to "stop sleeping" if you want a promotion. This review on Blind, however, has a more positive view on the role:
"I would say that DE does have reasonable WLB. I worked at FB as a DS which did not. DEs are paid the same but have much less meetings and responsibilities on their plate. They can just do their work and go home. It’s a pretty good role."
As with most positions at Facebook, it seems as though work-life balance really depends on the team you join, as does the impact of your work. On Glassdoor, one reviewer claims:
"If you join the wrong team, your work could be boring and meaningless."
In terms of salary, data engineers and data scientists are paid comparably. Both roles have similar base pay to that of SWE, but equity tends to be 60% of SWE.
You may already be aware that Facebook tends to have a quick promotion trajectory. Part of this is because the company holds 2 performance reviews per year that hold equal weight. Starting in 2022, Facebook will move to only 1 performance review per year, so the promotion timeline could slow down a bit. This may also lend itself well to fostering a better work-life balance.
One reviewer on Blind explains the idea behind promotions at Facebook:
"Facebook managers need to promote their directs or they get a bad rating for being bad at their job. There's a ~2.5y clock ticking to the next promo. It's the manager's job to find promo-worthy projects for you"
The general consensus among Facebook employees echoes the above review. Facebook managers help to promote you as soon as you're ready. At many other companies, such as Google, you have to self-promote and build a case for yourself, which ends up being a longer process.
You should know that Facebook has a time limit on how long you can remain at the same level before being fired. This typically applies to IC3 and IC4 where you have 2.5-3 years to get promoted. Once you reach IC5, the time limit no longer exists — it's generally difficult to be promoted above IC5 and many Facebook employees remain at this level for their entire time with the company.
So, what is Facebook looking for?
When asked how to get promoted as a data engineer on Blind, one user answered:
"Depending on level, they’re generally looking at a combo of impact across multiple teams, ability to identify a need and solve it, and a business case that merits a person of that level to do the work. Core skills are assumed to be table stakes, and you have to already be doing the job at the next level (backwards-looking promotion)."
On Glassdoor, a user responded:
"[You] have to create 'impact' and then market your impact in a political way to be promoted."
Promotions at Facebook typically happen through performance reviews. To prepare yourself for this process, read: Behind Performance Reviews + Bonuses at Facebook
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