Amazon Data Engineer job interview

This historical account describes Jason’s reported interview for a mid-level Amazon Alexa data engineer role. The interview date is not recorded here. Treat the sequence as one candidate’s experience and confirm current expectations with your recruiter.

Amazon Data Engineer job interview summary

How it gets started: internal referral from a former colleague.

Job Level: Mid 

Team: Alexa

Years of Experience: 4 years experience 

Degree: M.S in computer science

Offer: Yes

Compensation: omitted. The original figure was written as “~260 USD,” with no reliable basis for correcting its amount or units.

Location: Seattle, WA

Interview process: 6 weeks

Preparation: 3 months

Has a job: yes

Decide to join: N/A

Amazon Data Engineer Job Interview Round 1: recruiter chat

Basic information, most impressive project, team intro, past experience.

Amazon Data Engineer Job Interview Round 2: SQL coding

1. Write a function to return the cumulative spend of each customer (similar to SQLPad coding question #113);
2. Top 3 products vs. bottom 3 products (similar to SQLPad coding question #94)

Amazon Data Engineer Job Interview Virtual Onsite Round 1: data engineering and big data concept

1. How to debug a long-running SQL query?
2. Experience in Spark, what is sharding? How to partition data into different parquet files?
3. What python libraries have you used to work with S3? What about redshift? Have you ever used boto3?

Amazon Data Engineer Job Interview Virtual Onsite Round 2: ETL

1. Quick intro about yourself;
2. Design a data pipeline for a user report dashboard that shows the need to know top Alexa user requests by different countries every hour.

Amazon Data Engineer Job Interview Virtual Onsite Round 3: Data Modeling

1. What is star schema, what are its pros and cons?
2. What is a dimension table? What is a fact table?
3. Design the backend data house of a ridesharing app?

Amazon Data Engineer Job Interview Virtual Onsite Round 4: leadership

1. Tell me about a time you have to meet a tight project deadline?
   • Follow up: do you have a plan b, and why?
2. Have you ever failed at a project? Tell me about your biggest failure.
   • Follow up: what would you have done differently?

Amazon Data Engineer job offer

Jason reported hearing back about two weeks after the interview, receiving an oral offer, and then receiving a written offer after negotiation. The reported negotiation percentages were not independently verified and are not presented as a benchmark.

Prepare the pipeline design

For the hourly request dashboard, clarify whether an hour means event time or processing time, how to assign a country, and how to handle duplicate or late events. State the grain of the output: one country, one hour, and one request type before ranking. Discuss how a rerun avoids counting the same event twice and how you would detect missing input.

For cumulative spending, define the treatment of refunds and same-time purchases. For top and bottom products, decide how ties work and whether a product can appear in both groups when the population is small. These checks turn a memorized query into a defensible answer.