How To Prepare For A Data Engineering Interview

Interviewing for any technical position generally requires preparing, studying, and long-all day interviews. As a data engineer, what we need to study is not always clear. Some positions require Hadoop, others SQL, some roles require understanding statistics while still others require heavy amounts of system design.

I wanted to create a video to cover some key points for data engineer interviews.

This video will cover points such as data warehouse design, coding and behavioral questions. I wanted to give the viewer a good high level view of what you should prepare for.

If you enjoy this video on data engineering interviews and want more details, then please comment with your requests.

You can find the checklist here:

Interview query Article:

[venchia]

Very on point to focus on results rather than solely on tech achievements when showcasing a project. Not only at amazon but generally any big company wants someone that can not only lead technically but also earn trust from stakeholders and be business aware (e.g. know the success metrics and how to reach and improve on them). Well done sir! Not many views you are having for now but be consistent in posting this kind of content and surely the channel will grow in the near future :)

[phasematerialsresearch]

Would all of this be required for a Junior Data Engineering interview as well? A video on the junior position interview would be great.

[murugesanrm]

Thanks! Keep up the great work and looking forward to learn more from your channel!

[anushavenugopal]

Can you please go in more detail with respect to Datawarehouse design models for real life examples like you mentioned for Costco

[darkTranquillity]

One thing I've been trying to find out is, what is the upper bound in coding challenge complexity for a DE vs a SWE? I get asked anything between flatten a binary tree to a Linked List or something simple like find the first non repeating character in a string. Also, some DE technical screens don't include any SQL. It's all so arbitrary.

[aznfoever]

DW design video using the Costco example please! Thanks for this!

[niteshkamboj]

Awesome! Super informative and helpful.

[liangbinchen]

Great insight! I found it very helpful.

[vedanthasm]

Very good info!. Request you to do one Data Warehouse - Data modelling examples in detail

[tarunleekha]

Hey! Bro . Great video . It would be great if you can show end to end use case for like 30-40 minutes for any specific use case .

[ayushipatra]

Hi Benjamin,

Thank you so much for the checklist!! It really helps!!
Do you have any link or resources to get hands on experience on Data Warehousing? I am looking to get an intuitive thought process to create a data model for any particular business requirements. I am not able to query from the model mostly because I have only worked on OLTP side of it.

[siddharthsingh]

Hey! Bro. That's really a great video.

[anjalishar]

hi there, nice video my question is that is learnin hive, py spark, SQL and python good enough to crack an interview and to what extent is programming matter in cracking a job as a fresher?

[Retrosenescent]

I've never worked with streaming data (only batch) and never had to improve a pipeline's performance. Can you give your own examples of each so I have a better idea of what those entail/what you're talking about?

[amolnimbekar]

Airflow for logging? How? Do you mean orchestration. ?

[MrKaNuke]

Hey Ben did you ever do the example with Costco or DoorDash like you mentioned?

[murat]

The video is great! Thank you!
I heard that some of FAANG do two ETL rounds in their on-site interview. One of them is about batch and the other is about streaming use cases. Do you know about those type of interviews? I thought they only ask data structures and algorithm questions for Python part.

[golammuhaimeen]

what level of interview was this for? I'm guessing intermediate to advanced? what could I expect for a more entry level interview? Thanks

[jasparta]

6:59 why U said "sequel" not "S Q L". Yes, I also hate ppl which pronounce is as "skull".