March 09, 2022

Facebook data engineers are responsible for designing, implementing, and maintaining the data infrastructure that powers Facebook's massive social network. They work with petabytes of data and trillions of queries every day, so it's no surprise that they're some of the most sought-after engineers in the tech industry.

So, if you're lucky enough to land an interview with Facebook, you can expect to be asked some tough questions during the Facebook data engineer onsite interview and assessment process. The interview procedure is elaborate, and there's no point rushing through it to get a Data engineering position. So, give yourself more time to prepare for your interview by reading this guide.

Facebook Data Engineer Role 

The Facebook data engineer role is a complex one. As a data engineer at Facebook, you'll be responsible for designing and implementing the data infrastructure that underpins the social network. This will include everything from collecting and aggregating data to building models and dashboards to help business users make informed decisions.

You must be able to work with large datasets ( petabytes ) and optimize database performance to ensure that Facebook can continue to handle the trillions of queries it receives every day.

Minimum Required Skills :

• Strong experience with big data technologies, such as Hadoop and Spark

• Experience with database design and management (NoSQL and MySQL)

• Proficient in Python or Java for scripting purposes

• Experience with workflow management engines, such as Airflow

• Good understanding of data warehousing concepts

• Strong analytical and problem-solving skills

• Excellent communication and collaboration skills

These are just some essential skills to become a Facebook data engineer. A computer science degree or related field is typically required in terms of educational background. However, some companies may be willing to consider candidates with less experience case-by-case basis.

Facebook Data Engineering Teams 

Facebook comprises many data engineering teams, each with its own focus and area of expertise. Here's are some common data engineering teams at Facebook:

Data Warehouse:  This team is responsible for designing and implementing the data infrastructure that powers Facebook's business intelligence (BI) applications. It includes everything from data collection and aggregation to data modeling and dashboards.

(FAM) Facebook App Monetization: Data engineers in this team are responsible for collecting and analyzing data related to Facebook's app monetization efforts. It includes understanding how people interact with apps, what types of ads they respond to, and measuring the effectiveness of different monetization strategies.

Facebook Video Distribution: In this team, data engineers are responsible for collecting and analyzing data related to Facebook's video distribution efforts. It includes understanding how people consume videos, what types of content they're watching, and measuring the effectiveness of different distribution strategies.

Novi Blockchain Data Engineering: This team is responsible for collecting and analyzing data related to Facebook's blockchain efforts. It includes understanding how people are using blockchain-based applications, what types of transactions they're making, and measuring the effectiveness of different blockchain platforms.

Partnerships Central Systems, Tools, and Data Team: Data engineers in this team are responsible for designing and implementing the data infrastructure that supports Facebook's partnerships initiatives. It includes everything from collecting and aggregating partner data to building models and dashboards to help business users make informed decisions.

Family Ecosystems: The data engineering team in this group is responsible for collecting and analyzing Facebook's family of apps (Instagram, WhatsApp, Messenger, etc.). It includes understanding how people are using these apps, what types of content they're consuming, and measuring the effectiveness of different features and functions.

There are many other data engineering teams at Facebook, but these are the most common. You can check out the Facebook Careers website to learn more about specific teams.

Facebook Data Engineers Interview Process 

The Facebook interview process for data engineers consists of three rounds: Phone screen, onsite interview, and behavioral grounds. You will be asked basic questions to assess your technical skills on the phone screen. A Facebook data engineering team member typically conducts this round.

Onsite interviews are more in-depth and consist of technical and behavioral interview questions. Technical questions will focus on your knowledge of data engineering concepts, while behavioral questions will assess your problem-solving skills and how you work in a team.

The final round is behavioral rounds, which managers or other senior employees typically conduct. This round is focused on assessing your cultural fit at Facebook.

However, the most crucial part of the Facebook data engineer interview questions is the onsite interview. So let's discuss this further.

The Facebook Data Engineer Onsite Interview

Assuming you meet the minimum requirements, the next step in the phone screen process is usually an onsite interview. It will typically consist of technical interviews and a lunch with some Facebook employees.

The goal of the Facebook data engineer onsite interview is to assess your skills and knowledge related to big data, databases, Python/Java scripting, data warehousing, and ETL (extract, transform, load) processes.

You will be asked to solve several problems related to these topics, so you must be prepared for everything. It is suggested to study big data concepts, practice your coding skills, and familiarize yourself with the Facebook ecosystem.

That being said, let's look at some of the most common Facebook data engineer onsite interview questions.

Big Data 

• What is big data?

• How is big data different from traditional data?

• What are some of the biggest challenges with working with big data?

• How can we effectively process and analyze big data?

Databases 

• What is a database?

• How is a database different from a data warehouse?

• What are the most common types of databases?

• How can we effectively query databases?

Python/Java Scripting 

• What is Python/JavaScript?

• How do you write a Python/JavaScript program?

• What are some of the most common libraries for Python/JavaScript?

• How can we use Python/JavaScript to interact with databases?

Data Warehousing 

• What is data warehousing?

• Why do we need data warehouses?

• How can we effectively design data warehouses?

• What are the common types of data warehouse architectures?

ETL (Extract, Transform, Load) Processes 

• What is ETL?

• How is ETL different from traditional data processing methods?

• What are some of the benefits of using ETL processes?

• What are some of the most common ETL tools?

More Facebook Data Engineer Interview Questions

• Create a Facebook product or future building platforms for existing Facebook product

• Previous project experience

• Reporting tools like Excel and Tableau

• Big data solutions like EMR and Spark

• Visualization and metric solution designs

• Modeling and statistics

• DB performance tuning

• Data pipeline design

• SQL

• Algorithms and Data structure

These are questions that might be asked in a Facebook data engineer onsite interview. Remember that the company is constantly updating its interview process, so staying up-to-date on the latest trends is important.

Tips on Acing the Facebook Data Engineer Onsite Interview 

Now that we've covered the Facebook data engineer onsite interview let's discuss some tips to help you. Our top-rated recruiters at Recruitmently have compiled a list of tips to help you succeed.

Study on Big Data Concepts 

The best way to prepare for the Facebook onsite interview is to study the topic at hand. Make sure you understand the different types of big data, how it's processed and analyzed, and common challenges associated with working with large datasets. Familiarizing yourself with Facebook's ecosystem will also give you an edge in the interview.

Practice Your Coding Skills 

Coding questions are a staple in technical interviews, so you must be prepared. Take some time to enhance your Python or Java skills and familiarize yourself with the most common libraries. You should also be able to query databases effectively using SQL.

Prepare for Data-Related Questions 

In addition to coding questions, you will likely be asked data-related questions as well. Make sure you can differentiate database and data warehouse, common data warehouse architectures, and ETL processes. Familiarizing yourself with reporting tools like Excel and Tableau is also recommended.

Be Confident and Positive 

Last but not least, remember to be confident and positive throughout the interview process. The Facebook data engineer onsite interview can be daunting, but if you go in with a positive attitude and show that you're excited to be there, you'll be sure to impress your interviewer.

Ready for a Facebook Data Engineer Career?

If you desire a career in data engineering, Facebook is a great place to start. With its ever-changing interview process, it's essential to stay up-to-date on the latest trends. Recruitmently can help you do just that – our team of expert recruiters will help you prepare for your interview, provide career advice, and more. Sign up today and get started on your journey to a new career!

Do you have any questions about the Facebook data engineer interview process? Let us know in the comments below!