Amazon Data Manipulation (SQL/Python) Interview Questions
Practice 629 real Amazon interview questions for 2026. Covers all top categories — Coding & Algorithms, Behavioral & Leadership, Machine Learning, Data Manipulation (SQL/Python), and System Design — across Software Engineer, Data Scientist, Machine Learning Engineer, Product Manager, and Business Intelligence Engineer roles. Real Amazon interview questions from actual interviews with detailed solutions; use this collection for interview preparation that emphasizes shipping at scale, measurable impact, and the company’s Leadership Principles. Expect coding-heavy assessments for Software Engineer candidates: frequent tree and dynamic-programming problems, two-array optimization patterns, nested object/path lookups, and system-design prompts that mirror product flows (online Minesweeper, pizza-ordering, credit-card and shipping/cost systems), plus leadership and collaboration behavioral prompts. Data Scientist rounds concentrate on experimentation and metrics (A/B design, hand p-values, D7 retention SQL), RAG/recommender evaluation, and product-impact analyses. ML Engineer questions focus on production model design, LLM/agent concepts, reliability (cold start, training stability, online vs offline gaps), and large-scale detection pipelines. PM interviews stress customer-obsessed stories, ambiguity, Alexa product launches, and domain-specific data pipelines. Prepare with timed coding practice, end-to-end experiment writeups, STAR stories framed to Leadership Principles, and mock system-design sessions.
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Merge overlapping intervals
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Find LCA in a BST
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Choose Effective Graphs for Data Exploration
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Explain owning and debugging infra modules
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Describe projects and handle challenges
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Design an extensible ticketing system
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Count regions with DFS
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Design a risk management ticketing system
Design a Risk Management Ticketing System Context You are designing a ticketing platform used by human users (analysts, managers, admins) and an autom...
Compute reachability and minimal-time same-type scheduling
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Implement DFS and tree algorithms
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Find minimum days to deliver all orders
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Explain LLM architecture, tuning, evaluation
LLM Architecture, Positional Embeddings, Fine-Tuning (PEFT), Regularization, and Evaluation Context You are interviewing for a Machine Learning Engine...
Explain a research project in depth
Walk Through a Research Project You Led (End-to-End) Provide a concise, structured narrative that demonstrates scientific rigor, engineering depth, an...
Solve server updates and grid inconvenience minimization
1) You are given an integer array server of length n, where server[i] is the number of requests the i-th server can process. Over multiple days, you r...
Implement two array-cost minimization algorithms
Implement two array-cost minimization algorithms that appeared back-to-back in an AWS SDE online assessment. Each can be solved independently. Part 1 ...
Compute Latencies and Search Grid Path
You are given two coding tasks from an internship interview. Task 1: Compute Message Latency from CSV Logs Two systems, ComputeA and ComputeB, exchang...
Count partitions and equal-cost packages
Question Given a string itemCategories, count the number of ways to partition it into exactly two contiguous non-empty substrings (a prefix and a suff...
Describe Your Most Challenging Project and Its Outcome
Describe Your Most Challenging Project and Its Outcome Tell me about the most challenging project, situation, or thing you have worked on as a data sc...
Explain Decision-Tree Training and Clustering Algorithms
Explain Decision-Tree Training and Clustering Algorithms Decision Trees and Clustering: Training Mechanics and Core Principles Context Technical/phone...
Identify P-Value Limitations and Complementary Approaches
Identify P-Value Limitations and Complementary Approaches A/B Testing: Limits of P-values and Better Decision Practices Scenario Your team is running ...