Hello Fellow Data Engineers, Please guide me through this tough phase. I have been interviewing for past 4 to 5 months but didn't even get through the first round, let alone on site. Not sure what i am doing wrong but its so depressing. Never the less i lift myself up and keep grinding, hoping i will see light at the end of the tunnel. I am heavy on Sql,ETL,Google cloud/Big Query and Airflow. I picked up python from code academy and solved easy string related questions on LC. I have interviewed with Lyft, Affirm, Gusto, Facebook and some other companies. Failed at the tech screening. In retro, i realize there were some fairly easy questions which i didn't solve. People who recently interviewed for Data Engineer position. Can you PLEASE shed some light on your preparation strategy ? What areas of python should i focus and how can i sharpen my sql skills to solve fast? Please suggest the companies that you know hire/hiring DE. YOE - 5 years @Lyft @Facebook @Square @Amazon @Google @Apple @Twitter @Microsoft @Uber
If you have time to pickup or learn about spark/presto/snowflake/other and their differences/pros/cons, data modeling is fairly important as well, a bit of system design specific to data engineering
were the screening questions data engineering related or were they general leet code questions?
They were mixed. Sometimes take home challenges. Example, convert an input file to csv and load into table. but the file has messy data.
Are you already a DE? If you aren’t getting through the first round - it might not be a background fit for the larger companies. Obv also LC.
I am a DE. I guess my resume wouldn't be picked if there wasn't a background fit.
Just LC for few months. Datawarehouse design according to business requirements,SQL and Python
ETL on Hadoop/Spark or tools like informatica?
Informatica
start reading on hadoop, map reduce, spark.
Data Modeling is probably the single most important skill, besides SQL, to master for a Data Engineer. Every single company I've interviewed at wants your DM concepts to be crystal clear. A close second will be a good business/product sense. Coding questions are hardly ever of high difficulty. Data Engineers focus way too much on them while prepping because they don't usually actively code in their job. Here's my take on the important tech skills to master to crack DE interviews: 1. Data Modeling 2. Advanced SQL (performance tuning included) 3. Business/Product sense. Some companies call this module requirement gathering. 4. Programming. Strong basics - lists, dictionaries, tuples, strings etc. Don't waste time in tough problems.
how do you prep for data modeing when your interviewers ask you open ended questions and you need to derive kpis after building model ?? Any book/recommendations on data modeling questions?
The Data Warehouse Toolkit by Ralph Kimball. The only book you need.
OP, I am having the same issue as you stated. We are not allowed to use libraries like pandas in interviews which is generally used in day to day job. I couldn’t find much help from leetcode as well for data engineering.
LC as much as you can and that’s pretty much it nowadays honestly
Thanks for being honest.
not worth solving all questions for DE... focus on most asked and questions around string and array. If company asks you tree or graph or some wierd game programming question then that means they are looking for software engineer or hiring manager has less idea about data engineering.