Amazon | BIE Intern | Bangalore | Offer
Sharing my interview experience for the Business Intelligence Engineer (BIE) Intern role at Amazon, Bangalore. Hope this helps anyone preparing for a BIE/Data Analyst style role — the process is quite different from a typical SDE loop.
TL;DR: Resume screening → Online Assessment (MCQs + coding) → 2 interview rounds → Offer in ~2–2.5 weeks.
Round 0: Resume Screening
Applied On Campus and got shortlisted based on resume. Nothing to prepare here beyond making sure your projects are data-heavy and clearly written SQL, pipelines, dashboards, and anything analytics-adjacent stands out for this role.
Round 1: Online Assessment
Two parts:
1. MCQs — Mostly:
- Computer Fundamentals
2. Coding question — standard DSA-style problem. Nothing exotic; solid fundamentals were enough.
Round 2: Technical Interview 1
A fairly balanced technical screen.
SQL (medium level)
- Multiple query-writing problems, mostly medium difficulty
- Joins, aggregations,
GROUP BY/HAVING, window functions, subqueries
Data Modelling
- Fact vs dimension tables
- Star schema vs snowflake schema
- How I'd model a given scenario end to end
DBMS Concepts
- Keys, constraints, indexing
- Normalization, and where you'd deliberately denormalize
- ACID properties
Python (basics)
-
Language fundamentals
-
Simple data manipulation logic
-
Not to forget he asked me one dsa based question fairly easy but he wanted the code in python specifically.
Takeaway: Be able to explain your SQL, not just write it. The interviewer cared about why I chose a window function over a self-join.
Round 3: Technical Interview 2
The tougher and more interesting round.
Timed SQL sprint — 6 queries in 15 minutes
The interviewer put 15 minutes on the clock for 6 SQL questions:
- 3 easy
- 3 medium-to-hard
Speed genuinely mattered. There was no time to overthink syntax you have to know joins, aggregations, and window functions cold enough to type them out almost reflexively.He also asked me about dashboarding and lifecycle and few fundamentals of dashboarding like calculated columns etc.
DBMS concepts
- Few standard terminologies like schemas etc
- Normalization (normal forms, when and why to apply them)
- Related fundamentals
Project deep dive (a big chunk of the round)
- Detailed walkthrough of my project
- Lots of STAR-format questions: Situation, Task, Action, Result
- Why I picked the tech stack I did
- Challenges I hit and how I worked around them
- Trade-offs and what I'd do differently
Behavioral
- A few questions mapped to Amazon's Leadership Principles
Result
Heard back in about 2–2.5 weeks with the offer letter. 🎉
Location: Bangalore
What I'd Recommend Preparing
- SQL, then more SQL. Window functions, CTEs, ranking, aggregations, self-joins.
- DBMS theory properly. Normalization, schema design, indexing, ACID. Don't just recognize the terms — explain them and give examples.
- Data modelling. Star vs snowflake, fact vs dimension, and how you'd design a warehouse for a given business problem.
- Python basics. Enough for data manipulation and simple logic; you don't need deep DSA for the interviews (but you do for the OA).
- Your projects, in STAR format. Write out 3–4 stories in advance covering conflict, failure, ownership, and initiative.
- Leadership Principles. Map your stories to them before you walk in.
Happy to answer questions in the comments. Good luck!


