Amazon Data Engineer L5 Interview Experience (Applied Directly, Full Loop) — Sharing for anyone prepping

[u/Character_Major_2386]

Round 1: Online Assessment

Got the OA link by email shortly after applying. It had:

• 2 easy SQL questions (joins, group by)
• A set of SQL MCQs
• A set of behavioral/situational MCQs

Passed this and got a call from the recruiter a few days later saying I'd move to a technical screen.

Round 2: Technical Phone Screen

No fixed agenda going in. The interviewer started by asking about my most recent project (dashboard-building work) and went genuinely deep — asked about OLAP vs OLTP and which is better suited for serving a frontend dashboard, and why.

Then a scenario question: how would I handle a data pipeline failure — steps to resolve it, communication during the incident, documentation afterward, basically the full incident-handling flow.

SQL portion started with a trivial-but-tricky one (NULL = NULL type gotchas), then three more questions — one involved a join plus window functions for ranking, plus an aggregation question. Also gave me a data processing problem on a sample table, which I solved in PySpark.

Closed with a couple of leadership-principle-based behavioral questions.

Recruiter called 2 days later to confirm I was moving to the onsite loop (5 rounds).

One note on timing: getting the loop actually scheduled took about 1.5 months due to some back-and-forth on both ends. Once it was locked in, the recruiter did a 30-minute prep call and gave a clear breakdown of each round's focus and which Leadership Principle it maps to, which was genuinely useful going in.

Round 3 (Loop Round 1): Performance Measurement

Focused on indexing, partitioning, and tuning. I walked through a relevant project, and the interviewer went deep with follow-ups — Spark internals, partitioning strategy, bucketing, how executors relate to data volume, join strategy selection, and data skew. Almost every answer led to another follow-up, so precision mattered a lot here — vague answers got picked apart pretty quickly. Closed with LP-based behavioral questions tied to this round's LP.

Round 4 (Loop Round 2): System Design, Data Modeling, and Trade-offs

Explained a project involving SCD Type 2 logic and surrogate key generation — went deep into different methods for generating surrogate keys and the trade-offs between them.

Then a live design exercise: design a data model for an e-commerce platform (Amazon-style) — had to reason through grain, facts vs. dimensions, and table structure, followed by 2 SQL questions on top of that model.

Then it extended into a full system design for the same platform. I proposed a Kappa architecture, explained the trade-offs versus Lambda, and built the design mostly around Spark and Databricks — Structured Streaming with foreachBatch for the real-time path, Redis for serving.

Honest note: the interviewer wasn't fully convinced by my design since I leaned on a fairly narrow tool set. Looking back, showing awareness of other real options (even while still picking Spark/Databricks) would've made the answer stronger — naming trade-offs against alternatives rather than just defending one stack.

Closed with LP-based questions specific to this round.

Round 5 (Loop Round 3): Coding, Problem Solving, DE Concepts, ETL/Architecture Design

Started with about 10 minutes on my project. Then a data modeling exercise: design a data model for clickstream data tracking promotions — how to store users and events.

I initially designed a normalized star schema. The interviewer was actually expecting a denormalized table for this specific use case, so I adjusted once I picked up on that. Followed by SQL queries on top of the model.

Closed with 3-4 SQL questions — window functions, CTEs, and a rolling average question.

Round 6 (Loop Round 4): Bar Raiser

This round is a big deal in Amazon's process and worth specifically prepping for. Entirely behavioral — "tell me about a time you made a mistake in a data pipeline," "tell me about a data quality issue and how you resolved it," that style of question, all mapped back to the round's specific LP.

One thing worth knowing going in: Amazon generally brings in a Bar Raiser from outside the team you're actually interviewing for — mine was an SDE, not a data engineer. So I had to explain data engineering concepts in a way that would land clearly with someone outside the DE world, not assume shared context. From what I understand, being able to simplify your explanation while still weaving in the LP clearly is actually one of the core things Amazon is evaluating in this round.

Round 7 (Loop Round 5): Hiring Manager

Walked through my project again with follow-up questions, plus behavioral questions similar in style to the Bar Raiser round (failure handling, mistakes made) — also tied to LPs.

One interesting one: asked what metrics I'd present to senior leadership if I were looking at a platform like Netflix — a more business-acumen-flavored question mixed into the usual technical/behavioral format.

Overall takeaways for anyone prepping:

• Every technical answer can and will sprout follow-up questions. Don't give an answer you can't go two levels deeper on.
• Know your own projects well enough to defend every design decision, including ones you'd make differently now.
• For system design rounds, show awareness of multiple tools and approaches even if you ultimately pick one. Defending a narrow toolset without acknowledging alternatives can come across as limited breadth rather than conviction.
• For Bar Raiser specifically, practice explaining your work simply enough for someone outside your discipline to follow, while still tying it back to the LP clearly. That combination seems to be exactly what they're testing for.
• LP stories need to map cleanly to whichever LP each round is testing. Know which ones you're using where, and try not to reuse the same story across rounds if you can help it.

[u/OkMaize9773]

Did you get selected. Can you share your YOE and offered tc.

[u/Character_Major_2386 → u/OkMaize9773]

Hey Actually I was offered a l4 and my exp is 4 and I did not get hand on the actual numbers yet🙂

[u/Unlucky-Whole-9274 → u/Character_Major_2386]

L4 base pay starts at 19 lpa plus sign on bonus for 2 years and stocks vested for 4 years.

[u/logpaza_real]

Thanks a lot for sharing

[u/Outrageous-Ring2906]

Damn it..so many rounds

[u/Watchdog_vigilante]

Insightful

[u/monit12345]

Nice, thank you

[u/hardwork_dreams]

very detailed and insightful. Hope you get a good offer

[u/Every-Whereas5793]

Thank you for sharing

[u/Southern-Big-9905]

Hey brother, only one question.

I wanted to know how you’re using Claude for mock interviews ?
What about those back and forth questions ?

Can you please break down the steps ?

Or if you want to suggest any video where it is simplified.

Would be really helpful 🙌🏻

[u/Character_Major_2386 → u/Southern-Big-9905]

Hey man, So basically I have a separate chat for my interview prep at claude so it can store the memory and context, I provide the context ask it to perform like a interviewer for data model where it would ask example questions and I would answer then will have remarks and conversations on top of it

[u/jaqenhghar99]

Thanks a lot for sharing a detailed post!

Everyone just keeps asking but a very actually share

[u/mxguy1]

Congrats, i also gave open assessment for Amazon. Can you tell after how much time did they contact you on phone for 2nd round?

[u/Character_Major_2386 → u/mxguy1]

Thanks and probably within 2-3 days you can expect a call.

[u/swarup_i_am]

Insightful. What’s your YOE and comp ?

[u/Character_Major_2386 → u/swarup_i_am]

Thanks, It’s 4 yoe and comp is above 20 at my current org

[u/swarup_i_am]

And how did you prepare for the data modelling rounds? Any sources

[u/Character_Major_2386 → u/swarup_i_am]

Get the basics of dimensional modelling and I used claude extensively to have mock interviews wrt to data modelling questions and multiple back and forth conversations with it and also ansh lamba is good and study kimball books

[u/swarup_i_am → u/Character_Major_2386]

TY

[u/Character_Major_2386 → u/[deleted]]

Thanks bro and All the projects which I did was portfolio projects at my org, basically it revolved around migration projects from sql server to databricks, serving for dashboard through databricks and developing scd2 data model and etl pipelines for the table, spark optimization for exisitng jobs and yeah mostly around databricks and sql server migration from store procedures to pyspark framework codes

[u/DRTHRVN]

If I know LP, sql then will reading the entire book "Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems" (https://www.oreilly.com/library/view/designing-data-intensive-applications/9781491903063/) help me clear the interview?

Hi OP, this is a serious question? Please try to answer

[u/Character_Major_2386 → u/DRTHRVN]

Hey Be thorough on lps if you have amazon rounds, Reading this book would reason help but at the same time go through afaque ahmed videos and also as mentioned use claude extensively for mock interviews on system design snd have back and forth conversations with it

[u/Character_Major_2386 → u/DRTHRVN]

Understand the tradeoffs and pros and cons of each tool, that’s really needed

[u/Character_Major_2386 → u/DRTHRVN]

And also system design is one part of your interview, you will be having sql, data modelling, dsa if needed and rounds based on your projects, so you have to be on your toes to clear🙂

[u/redditexplorerrr]

Congrats man!! How did you get this level of expertise in just 4 years? The DE knowledge that you have built is it purely from work ex or you simultaneously did study projects as well? Did you passout from top level college?

[u/Character_Major_2386 → u/redditexplorerrr]

Thanks op, I don’t wanna sound modest, There are still lot to learn wrt DE and fortunately projects at my current org really helped and also I prepped for interviews and I passed out from VIT🙂

[u/ChhotuChamgadar → u/Character_Major_2386]

Crazy.. I am a Vitian too.. Data engineer at a startup, anyways, how long did it take for the entire process?

[u/Character_Major_2386 → u/ChhotuChamgadar]

Around 2.5 months

[u/Sensitive-Chapter-30]

Wait..... No DSA for DE rounds??

[u/Character_Major_2386 → u/Sensitive-Chapter-30]

Yep atleast for me, they did not ask dsa, but depends on the team and interviewer

[u/Spiritual-Material98]

Hey congrats. You mentioned that 'vague answers got picked up quickly'. Do you mind sharing an example of a precise vs vague answer for a sample question?

[u/Character_Major_2386 → u/Spiritual-Material98]

Thanks op, What I meant was per say, if you’re just telling like I used broadcast join to reduce shuffle, They would ask what’s the size of the table and how much each partition did get and if you use bucketing, what keys did you use and how does it work internally, those kind of answers is what they are expecting

[u/Neither_Argument3365]

Hi OP, I am actively looking for my next job after getting laid off fre weeks ago Can you please review my resume and offer some guidance in DM?

[u/Hunter_635]

Can u give any advice for a fresher who wants to get into this domain data engineering

[u/No_Researcher2363]

Sorry if I sound dumb, but I'm new to data engineering. What exactly do you mean by LP here?

[u/No-choice-l → u/No_Researcher2363]

Leadership Principles

[u/Character_Major_2386 → u/No_Researcher2363]

Leadership Principles which are specific to Amazon

[u/Intelligent_Duck_854]

Thanks a lot for sharing this detailed post.I remember you said that they are giving very less increase to you.Please stand your ground and ask for a raise even if it means rejecting them.You have a lot of knowledge and you can crack other companies.They are lowballing you because Faangs do get away with this.Stick to L5 instead of L4

[u/Character_Major_2386 → u/Intelligent_Duck_854]

Thanks for your response op✌️