Initial Screening
3 SQL 3 Python
SQL:
Star schema, sales transaction fact, book author etc dims
* Identify authors who have published at least 5 books
* Calculate the percentage of total sales completed on the same day the customer registered
* Find customers who purchased 3 or more books on both the first and last day of sales, excluding those with only one transaction
* Find the IDs of the top 5 customers, ordered by average payment per book made by the people they invited
* Find the total number of authors registered with the bookstore. What percentage of them have a website URL that contains ".com", and what percentage never made a sale?
* What was the total value of sales and the number of unique paying customers, grouped and sorted in descending order by payment type?
* Having a transaction table find the sum of total orders and the count of unique customers
Python:
* Calculate the average book price from a list of prices
* The bookstore gathered a list of customer comments from each shop location
and wants to find the most common comment across all locations (ignoring duplicates from the same location). If multiple comments appear the same number of times, return any one of them.
* Search an element in an unsorted list
* Given a list of workshops, return the largest number of classes that were hosted in total across any consecutive years that had at least one workshop each.
5 sql
5 data structure and algorithms
25 mins each
They won't go to the next problem until one is done and expected results are met
Interviewer was very professional and tried to guide to think through the problem
Wen through standard screening call then the TA. The TA was a much higher difficulty then the prep guide. Not so much the difficulty of the question from a technical perspective, but understanding what the question was actually asking for. Example would be a problem like bookstore checkout system, but the explanation of it was sort of vague and the interviewer didn't really help me clear it up.
Starts with a screen, followed by leetcode style SQL+Python questions, Full loop of SQL, Python, SQL plus Python and lastly behavioural round. Every round is also an architecture round in some sense.
Data Engineer applicants have rated the interview process at Meta with 3.2 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 65% positive. To compare, the company-average is 56.5% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Engineer roles take an average of 35 days to get hired, when considering 365 user submitted interviews for this role. To compare, the hiring process at Meta overall takes an average of 31 days.
Common stages of the interview process at Meta as a Data Engineer according to 365 Glassdoor interviews include:
Phone interview: 41%
One on one interview: 20%
Skills test: 16%
Presentation: 9%
Group panel interview: 5%
Other: 3%
IQ intelligence test: 2%
Background check: 2%
Personality test: 2%
Drug test: 1%
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