The Amazon Data Engineer interview process typically consists of the following stages:

1. Online Assessment (OA) [If Applicable]

   • May include SQL, Python, or Data Structures and Algorithms (DSA) questions.
   • Expect medium to hard-level LeetCode-style problems.

2. Recruiter Screening (30 min)

   • Discussion on your experience, resume, and interest in the role.
   • Basic SQL and data engineering questions.

3. Technical Interview (1-2 Rounds, 60 min each) Each round typically consists of:

   • SQL: Write complex queries (JOINs, WINDOW FUNCTIONS, AGGREGATIONS, CTEs).
   • Python/DSA: Solve medium-level LeetCode problems (arrays, strings, hashmaps).
   • Data Modeling: Design a schema for a given use case.
   • ETL & Big Data: Questions on ETL design, data pipeline optimization, and distributed systems (AWS Glue, Spark, etc.).

4. System Design Interview (1 Round, 60 min)

   • Design a scalable data pipeline for a real-world scenario.
   • Discuss batch vs. streaming processing, data storage, and performance optimizations.

5. Behavioral Interview (1-2 Rounds, 45 min each)

   • Amazon’s Leadership Principles are key.
   • Expect STAR method questions related to challenges, decision-making, and ownership in past projects.

6. Hiring Manager Round (Optional)

   • Deep dive into your experience, projects, and long-term goals.
   • High-level discussions on data engineering best practices.

7. Offer & Negotiation If successful, you’ll receive an offer with details on compensation and benefits.

Would you like me to help you prepare for any of these rounds?

LeetCode medium level