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?