Process
I was reached out to by a recruiter via email and scheduled a phone call interview. Next, I had an on-site interview where they gave me enough time to prepare. Prep calls are the best. They gave me a very brief mock interview process for product sense.
Questions
Main focus should be on product sense, SQL, and basic Python, specifically lists and dictionaries.
SQL: You should be well aware of aggregations and how to perform a one-table scan to provide aggregated values.
Product sense is something that will be covered in all your interview rounds.
Data Modeling: Focus on how you design dimension and fact tables. Make sure to have denormalized fact tables. Review data models from Uber, DoorDash, and LinkedIn (at a high level, not like graph databases).
SQL questions will be based on your design approach.
Python: Basic questions, such as calculating averages and traversing/sorting lists and dictionaries, would be sufficient.
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Interview Statistics
The following metrics were computed from 347 interview experiences for the Meta Data Engineer role in United States.
Success Rate
Meta's interview process for their Data Engineer roles in the United States is extremely selective, failing the vast majority of engineers.
Experience Rating
Candidates reported having very good feelings for Meta's Data Engineer interview process in United States.
Meta Work Experiences
- 4.0Great people, culture, environment, and interesting projectsData Engineer • Current EmployeeMenlo Park, California, United StatesNovember 11, 2015Pros: - Everyone is smart, but most are also extremely friendly and willing to help/give advice. - Choose work that interests you, and managers do everything to make sure you are happy. - Flexible work hours (choose your own start and end time, doesn't matter how long you're in the office, really) within reason. - Great benefits, etc.Cons: - Steep learning curve. - Very hard to find good documentation when trying to learn about various aspects of infra. - A lot of custom systems and tools everywhere can be overwhelming to new hires. - Sometimes people move too fast and create projects without enough consideration for effort versus impact. - Compensation is probably not as good as other similarly sized companies for new grads (unless you are an extremely desired engineer with many competing offers).
- 5.0Sweet Place to WorkData Engineer • Current EmployeeBoston, Massachusetts, United StatesJanuary 27, 2019Pros: They treat you like a human here - amazing managers and the ability to choose teams.Cons: A lot of complex technology to pick up.
- 5.0Great place to workData Engineer • Current EmployeeMenlo Park, California, United StatesJune 26, 2023Pros: Competitive, fast-moving environment with a very open culture.Cons: Change in perks and layoffs are disheartening.
Meta Interview Questions
