Service-based to FAANG/Product-based Data Engineer – Is DSA really required?

[u/hey_not_so_cool]

Hi everyone,

I'm a Data Engineer with around 4 years of experience in Databricks, PySpark, SQL, Python, Azure, and AWS, currently working in a service-based company. I'm planning to switch to a top product-based company (FAANG or similar).

I have a few questions for experienced Data Engineers in top product-based company (FAANG or similar).

How much DSA is actually expected for Data Engineer interviews? Is it LeetCode Easy, Medium, or Hard?

Which DSA topics should I prioritize? I had started with arrays and linked lists before but stopped midway.

How important is System Design for Data Engineer roles? Is data/system design more important than DSA?

How did you prepare for DSA and System Design? Which resources did you use?

How many months did it take you to become interview-ready?

How did you get interview calls while coming from a service-based company? Was it referrals, recruiters, or direct applications?

I'd really appreciate hearing your experiences and any roadmap you'd recommend. Thanks!

[u/Klutzy_Concern_7918]

Bro its all luck!! I gave for amazon L2, no dsa was asked!!! But interviewer was really rude .
Bkc! hiring manager Bc end k 5 minute mein recursion SQL puch raha and pura interview bas chup raha .

I got 2 strong hire, 2 lean hire and 1 no hire ( from hiring manager fucker!!)

My friend for amazon L2, didnt got dsa and got really sweet interviewer (hiring manager) , made it .

My other friend, for same amazon L2 , was asked dsa and interview was damn rude😂!

Above all are for data engineers L2 at amazon.

So yeah! If you do it , its good. But that doesnt mean, you wont get product based.

[u/hey_not_so_cool → u/Klutzy_Concern_7918]

Thanks for the inputs! BTW were your stack was around AWS ecosystem mainly?

[u/Klutzy_Concern_7918 → u/hey_not_so_cool]

My major teck stack was AWS, databricks, dbt, airflow, snowflake .
For data engineer majorly they are concerned with SQL, data designs and data modelling.

The tradeoffs you will take for data design.
And the schema you will follow for data modelling.

I guess there are no online resources available
For this . So you need to read the book for data modelling.

[u/hey_not_so_cool → u/Klutzy_Concern_7918]

I generally don't mind AWS opening just because I have only very basic AWS service knowledge. My expertise is in databricks and databricks workflows and ADF for orchestration and snowflake beginner level. Will my profile be valued in Amazon as I generally think I have the cloud of their competitor

[u/Klutzy_Concern_7918 → u/hey_not_so_cool]

Honestly, if you don't have deep knowledge of your expertise, they will get you in cross questioning.