I applied for the Data Engineer, Analytics (University Grad) position via a recruiter. I initially interviewed for an internship last summer but was unsuccessful. However, my recruiter forwarded my resume to colleagues, and a position matching my profile became available, leading to me being contacted by another recruiter.

Similar to what others have mentioned on Glassdoor:

1. HR Screen: This involved a set of questions, answerable with one word or true/false, to check basic knowledge in Programming and Databases. Examples included: "When a program calls itself, what is it called?" and "What do you call a loop that never ends?"

2. Phone Interview: This 45-minute interview included 5 SQL and 5 Python questions. I completed all 10 questions within approximately 35 minutes. The interviewer was very interested in my thought process and provided assistance on one or two problems where I got stuck. I received an invitation for an onsite interview immediately, within about 1-2 hours of the phone interview. The questions were similar to those posted by others on Glassdoor, covering Python topics like Recursion, While Loops, Dictionaries, and Lists, and SQL topics such as Group By, Subqueries, and Joins.

3. Onsite Interview: I was invited to the Menlo Park office for three 1-hour full-stack interviews and a 1-hour lunch interview. The questions involved identifying the right metrics to solve given problems, SQL modeling, ETL process design, and writing algorithms/programs in a language of my choice. The lunch interview was casual, with questions like "Why Facebook?" and "Best day at work?" I was able to provide solutions to all the problems presented. At the end, interviewers allowed me to ask questions. I did get stuck a few times, but the interviewers offered tips to help me work through the problems. It's crucial to clearly explain your thought process, as they are interested in your problem-solving capabilities at scale and how you approach large-scale issues. The onsite interview questions accurately reflected the types of problems you would solve at Facebook. The preparation resources provided by my recruiter were excellent and mirrored the interview questions.

I waited almost three weeks for a response, as it was during the Thanksgiving holidays. Afterward, my recruiter called to inform me that I had received an offer for the Data Engineer, Analytics role at the Menlo Park office.

Resources: To improve my programming skills, I practiced on sites like LeetCode and HackerRank. Interview Cake's materials also helped me prepare for the interview. Reviewing various visualization examples would also be beneficial. I also studied recent Facebook Quarterly Results to understand the metrics that matter to them and explored their Engineering Blogs if time permitted.

Python:

• Count words
• Count substring
• Separate list of lists
• Random number generator