Amazon · Data Engineer (New Grad)
Amazon's new-grad Data Engineer loop centers on SQL, data modeling, and building reliable pipelines, wrapped in the same Leadership Principles behavioral bar as its SWE loop. Expect strong SQL rounds, data-warehouse and dimensional-modeling questions, ETL/pipeline design, one coding round, and deep STAR-driven behavioral questioning. Interviewers grade you on whether you can design correct, scalable data systems and reason about large-scale, sometimes messy data — while owning outcomes the way every Amazon role demands.
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What this interview tests
- SQL fluency (joins, window functions, funnel/cohort queries)
- Data modeling (star schema, fact/dimension, SCDs)
- ETL and pipeline design (batch vs streaming, idempotency)
- Handling large-scale, late, and dirty data with recovery
- One coding round (Python / algorithmic fundamentals)
- Leadership Principles expressed through STAR stories
Common question themes
Write a window-function query for a funnel or cohort
Design a star schema and justify fact vs dimension tables
Design a pipeline: batch vs streaming, idempotent reprocessing
"How would you handle late-arriving or duplicate data?"
"Tell me about a time you took ownership of a data problem"
A Python / algorithmic coding problem
Modeled on a public Amazon new-grad Data Engineer posting