Mix of great culture and impact with poor decisions (from execs & leadership) in critical times
Mix of great culture and impact with poor decisions (from execs & leadership) in critical times
Great Culture of Openness and Sharing Ideas. Best Place to Own Your Work and Contributions. Great Growth Opportunities. Great People to Work With. Amazing Impact of Work with Billions Users Globally and World's Greatest Tech Products. Great Scale and Tech Stack.
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Poor decisions occasionally by execs and leadership that do not make sense in terms of company long-term success.
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Laying off 20k+ talented employees when you have one of the largest profit margins in big tech companies simply does not make sense for the long-term success of the company (from financial, public reputation, employee morale, ethics, etc.).
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Poor efficiency implementation models. As a big tech company, it is expected to make much better long-term decisions using data. However, the decisions are made based on old models for short-term gains, which is very ineffective long-term.
Poor decisions are occasionally made by execs and leadership that do not make sense in terms of company long-term success. Meta has great profit margins, and its employees generate much more revenue for the company compared to their cost. (Revenue generated by N employees is more than 3X higher than compensation for those N employees, on average).
Laying off 20k+ talented employees (considering the above equation, recruiting & onboarding costs, etc.), where you have one of the largest profit margins in big tech companies in the world, simply does not make sense for the long-term success of the company (from financial, public reputation, employee morale, ethical, long-term growth, competitiveness, etc., perspectives).
Poor efficiency models are implemented. As a big tech company and a data-driven company, it is expected to make much better data-driven long-term decisions. However, the decisions are made based on old models for short-term gains, which is very ineffective long-term.
(Some examples:
- Investing enormously in Metaverse without having a strong and reliable long-term financial plan for ROI.
- The cost of laying off a massive amount of employees could be much higher long-term compared to its short-term gains.)
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Senior Data Engineer
This was a 7-round interview process for an L6 (Senior) / L7 level Lead Data Generalist Data Engineer role. The recruiters were very helpful. This role was for a senior-level lead position focused on a couple of new, confidential initiatives. The i
Senior Data Engineer
A recruiter spoke to me on the phone and gave me the position's details and the interview details. She told me the following interview would have questions in Python and SQL.
Senior Data Engineer
The process was smooth, beginning with a recruiter call, followed by a final loop of six interviews. There was also an informal round where I spoke with a random engineer about work-life at Meta. The entire process was easy and comfortable.
Senior Data Engineer
Menlo Park, California, United StatesAugust 1, 2021This was a 7-round interview process for an L6 (Senior) / L7 level Lead Data Generalist Data Engineer role. The recruiters were very helpful. This role was for a senior-level lead position focused on a couple of new, confidential initiatives. The i
Senior Data Engineer
June 4, 2026A recruiter spoke to me on the phone and gave me the position's details and the interview details. She told me the following interview would have questions in Python and SQL.
Senior Data Engineer
United StatesJuly 20, 2024The process was smooth, beginning with a recruiter call, followed by a final loop of six interviews. There was also an informal round where I spoke with a random engineer about work-life at Meta. The entire process was easy and comfortable.
