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:

1. For the coding portion, should I expect Python code related to ETL tasks or more challenging LeetCode-style problems?

2. 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?

3. Is the Python code in the onsite interview generally more complex than what was asked in the phone screen?

4. 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