Interview Prep Guide

Additional context

This document serves as a guide for aspiring Data Engineers preparing for interviews at Meta. Data engineering is a crucial and rapidly growing field focused on building and maintaining the infrastructure that allows organizations to collect, store, process, and analyze vast quantities of data. Data Engineers are in charge of building data pipelines, which are automated systems that ingest data from various sources, transform it into a usable format, and load it into data warehouses or data lakes for analysis. Their work underpins many data-driven processes, from business intelligence and reporting to machine learning model development. Companies like Meta rely on data engineers to maintain data quality and accessibility, ensuring that data scientists and analysts can efficiently extract insights and build data products.

The skills assessed in the Meta interview process, such as SQL and Python, are fundamental tools in the data engineering toolkit. SQL (Structured Query Language) is essential for querying and manipulating data stored in relational databases, while Python is a versatile programming language used for data processing, automation, and building data pipelines. The emphasis on efficiency and problem-solving reflects the demands of real-world data engineering, where engineers are often faced with complex data challenges requiring them to optimize performance and scalability. This guide builds upon the vast amount of open source knowledge, documentation, and community best practices, as well as internal Meta resources, to help candidates be successful in their data engineering interviews.

Data Engineer, Product Analytics

Initial Interview

Welcome to your Meta Data Engineer initial interview prep guide. This document covers what to expect and how to prepare for your interview. Use the table of contents below to find key sections quickly. If you have specific questions, reach out to your recruiter, they're here to help!

What you'll find in this guide

Data Engineering at Meta

As a Data Engineer at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications.

2 Definitions

Definition 1: Data Models: Conceptual representations of data objects and the relationships between them, used to organize and structure data within a database or system.

Definition 2: Queries: Requests for data or information from a database or information system.

In this role, you will collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way. You will design, build and launch new data models and visualizations in production, leveraging common development toolkits. Additionally, you will independently design, build and launch new data extraction, transformation, and loading processes in production, mentoring others around efficient queries.

Data engineers must have strong product awareness, strategic thinking, and prioritization skills, balancing daily support with long-term projects.

By joining Meta, you will become part of a world-class data engineering community dedicated to skill development and career growth in data engineering and beyond.

Interview process overview

This guide will explain what to expect during your initial technical interview with Meta. Your recruiter will be your guide throughout the process and aim to adequately prepare you to bring your best self to your interview.

What will your interview process include?

Definition

CoderPad: An online collaborative code editor and interview platform.

Your initial screen will be a 60-minute Zoom interview, during which you'll share your solutions on your computer via CoderPad, an online code-sharing interface. Prior to your interview, please familiarize yourself with the CoderPad interface; you can check out CoderPad's Tips and Tricks as you're preparing. Please ensure you join your custom CoderPad link a few minutes before your interview (our Coordination team will send you this link upon confirmation of your interview date / time). Please also make sure that you have strong phone and internet connectivity in a quiet zone.

Your conversation our interviewer will be divided into the following: - Introduction: 5 minutes - SQL screen:25 minutes - Python screen : 25 minutes - Questions and closing : 5 minutes Keep in mind throughout your prep that speed and efficiency are important. Practice with time constraints while you're working through the SQL and coding questions so that you are prepared for both your SQL and coding screens during your interview.

Best practices for video interviews

- Make sure you're in a quiet environment. - Test your equipment and connection before the interview. - If you can't hear or understand, request clarification or ask the interviewer to speak more slowly. - You'll need a laptop with a webcam, speaker, and mic. We recommend using a headset or headphones with a mic for better quality audio, but this is optional. - While we embrace the usage of advanced tooling in our day-to-day work to build the future of social connection, we ask that you not use any unauthorized outside assistance during interviews. Throughout the interview process you may be asked to share your screen via Zoom. Here you can find guidance on how this works.

Additionally, we ask that you disable and not use filters during your interview. This will help us get an understanding of how you approach problem-solving and coding independently. Outside assistance includes, but is not limited to, consulting external resources, seeking help from others, or using AI tools unless provided by Meta. - For your interview, ensure Zoom screen sharing is enabled in advance, as setup may require a few minutes. Here's how: Enable Zoom screen share. - A filter is considered any tool/feature that applies visual effects to your video feed, including virtual/blurred background.

Interview Dress Code

As you're probably aware, we promote a casual environment at Meta so that everyone can be their authentic selves. Formal dress is not required (jeans are definitely ok!). Dress comfortably. We care about what you can do, not what you wear.

SQL Screen

What can you expect?

3 Definitions

Definition 1: Schema: The structure of a database, including the organization and relationships between tables and fields.

Definition 2: ANSI SQL: A standard language for accessing and manipulating databases.

Definition 3: PostgreSQL: A powerful, open-source relational database management system (RDBMS).

Your SQL screen will be 25 minutes, where you'll have an opportunity to work through several questions. The purpose of this screen is to evaluate your understanding of fundamental SQL concepts. We will ask you to write a series of SQL queries using a PostgreSQL database, yet knowing standard ANSI SQL is sufficient for the interview. Working with a business-related schema and dataset, we will ask you to write SQL to help answer various business questions.

How to Prep

The Appendix / Resources section contains links to practice SQL interview question samples. Be prepared to cover fundamental SQL concepts: - Joins (inner, left / right outer, full outer, cross) - UNION versus UNION ALL Correlated subqueries - Aggregations - “Where” versus “having” Case statements - Filters - Groupings - Rankings - Verifying results and taking care of exceptions and NULL handling

Python Screen

What can you expect?

The Python coding screen will be 25 minutes, during which you'll have an opportunity to work through several questions. We recommend practicing the coding interview question samples listed in links in the Appendix / Resources section.

Definition

Dynamic Programming: An algorithmic technique for solving optimization problems by breaking them down into simpler subproblems and storing the results to avoid redundant computations.

How to prep You will be tested on your ability to develop an algorithm that solves the problem and passes multiple test cases. These problems will require an understanding of: Common data structures, such as: lists, dictionaries, sets, strings, and objects. - Algorithmic approaches, but do not require familiarity with specific algorithms (like Dijkstra's) or advanced techniques (such as dynamic programming).

Final tips for your interview

- Have a clear picture first and think out loud. Briefly describe your planned approach to the interviewer first. Jumping straight into coding without having a clear idea on what you want to do, or changing your mind halfway through, could slow you down.

It helps your interviewer follow along and learn about your problem-solving skills. They will want to understand why you're making certain decisions. (For example: Why subqueries instead of joins?) - Don't worry about things like typos, syntax, etcetera Some people have the right code sitting there, but they take another minute or two going over everything manually trying to check if it's all correct. Feel free to hit "run" to see what error messages come up. If you aren't sure about syntax, just ask the interviewer: "What's the syntax to check if an element is in a list again?" - Optimization. You should first try to come up with the correct solution.

If it is suboptimal, your interviewer will ask you to optimize it. - Be open. Interviewers are asking questions that are not meant to stump you, but rather they're meant to get to know your skills and gauge how in-depth your knowledge is. It's OK not to know something. Communicate openly with the interviewer, approaching questions as a chance to collaborate with them. - Listen for hints. Interviewers might ask questions such as, "Are you sure you want to use a loop there?"

This gives you an opportunity to consider alternatives to how to solve the problem, and to demonstrate that you can learn on the spot and implement feedback. - Questions. You'll most likely have some time at the end for questions for your interviewer. Some people find it easier to come up with a few questions in advance rather than thinking of them on the spot.

Post interview – What to expect

You can expect your recruiter to provide a specific timeline or updates along the way. Your recruiter will inform you of next steps after your interview as soon as they are available. Feel free to follow up with them if you have not heard within a week of your interviews.

At any time during the interview process, you can track your status, send thank-you notes and update your personal information via your career profile.

Appendix / Resources

Meta data engineers collected some helpful resources with content and activities for your initial tech screen. Take a look through the list as you prepare, and practice these problems. Think of these practice problems as a baseline, and if you have trouble solving them, then you may want to give yourself more time to prepare.

SQL Prep Resources - PostgreSQL Exercises - sqlzoo.net URL - SQL Course - Programmer Interview SQL Practice Database Mode Analytics SQL Tutorials - SQL Tutorial

Coding Prep Resources

HackerRank CodingBat LeetCode - Python for Everyone Course - Python Data Structures Course

Meta Resources

About Meta website Meta Newsroom website Meta Careers website and Meta Careers for Interns & New Graduates website Culture at Meta website Meta employee benefits website - Interviewing at Meta: The keys to success blog

Accommodations process

Meta is committed to providing reasonable support (called accommodations) in our recruiting processes for qualified candidates with disabilities, physical conditions, mental health conditions, neurodivergence, sincerely held religious beliefs, pregnancy, childbirth, or related medical conditions, as required by law. If you need assistance or require an accommodation, reach out via the Accommodations request form.

Thank you for taking the time to review this guide, we hope you feel prepared and excited for your interview!

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