Greetings,
I would appreciate it if someone from the community could help me prepare for my upcoming data engineering onsite interview for Product Analytics. Could you please provide insights on the following:
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For the coding portion, should I expect Python code related to ETL tasks or more challenging LeetCode-style problems?
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According to the practice guide shared by Meta, the Python coding standards seem quite high, comparable to what's expected for a core SDE role. Is this accurate?
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Is the Python code in the onsite interview generally more complex than what was asked in the phone screen?
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In the phone screen, the SQL problems were based on a single schema. Do they use a similar structure for the onsite interview as well?
I would greatly appreciate any guidance you can provide to help me prepare effectively for this interview. Thank you in advance for your assistance.
Update - Completed the Onsite Interview
Round 1 - Ownership - All about Why, When, Situation related to past experience. Example - Tell me a time when you had a conflict and took a data-driven decision, etc.
Round 2, 3, 4 - Coding/Technical:
1. Product Sense - Find the Success Metrics for Project XYZ (Mostly based on Lyft/Twitter/Video theme)
2. Data Model (Dimension/Fact)
3. (Easy/Medium) SQL based on the same theme
4. 1 Python Streaming with core data structure (Easy)
Rejected - The bar for the Ownership interview was not met.
Thanks
