🎯 Data Engineering Challenge

AI-native LeetCode for data engineers

AI-powered grading and hints used responsibly to keep it challenging and fun

Need Help?

Stuck on a question? Get help from the community!

Post on r/dataengineering

Also try: r/PostgreSQL • r/sql • r/devops • r/bigdata • r/statistics

How It Works

1

Answer Questions

Work through objective and subjective questions covering key data engineering concepts

2

Get AI-Powered Feedback

AI used responsibly and smartly—providing the right help at the right time to keep the challenge fun while ensuring accurate learning

3

Learn & Improve

Push yourself with challenging questions designed by experts. AI helps when you need it, but never takes away the fun of solving problems yourself

Topics Covered

SQL & Databases

Master SQL queries, database design, normalization, and optimization techniques

Statistics & Analytics

Essential statistical concepts for data engineers: distributions, hypothesis testing, sampling, and data analysis fundamentals

Data Modeling & ETL

Learn Extract, Transform, Load processes and data modeling best practices

Data Warehousing

Understand data warehouse architecture, star schemas, and dimensional modeling

Big Data Technologies

Explore distributed systems, Hadoop, Spark, and modern data processing frameworks

Data Pipeline Design

Design scalable, reliable data pipelines with error handling and monitoring

Data Quality & Testing

Implement data quality checks, validation, and testing strategies

Key Features

🧠

AI-Powered Grading

AI used responsibly to keep challenges fun and learning accurate. Expert-designed questions ensure error-free learning while maintaining the right level of difficulty

💡

Progressive Hints

Receive helpful hints when you need them, without spoiling the learning experience

🗄️

Comprehensive Topics

Cover SQL, databases, statistics, ETL, data warehousing, and data pipeline design

📶

Offline Support

Practice anywhere with offline-first architecture and local data persistence

Who Should Use This

Data Engineers

Whether you're a junior engineer building foundational skills or a senior engineer preparing for interviews, our quizzes help you practice and assess your knowledge across all levels.

  • ✓ Skill assessment
  • ✓ Interview preparation
  • ✓ Knowledge gaps identification

Software Engineers

Transitioning to data engineering? Our platform provides a structured way to learn data engineering concepts and validate your understanding before making the career switch.

  • ✓ Career transition support
  • ✓ Foundation building
  • ✓ Practical skill validation

Engineering Managers

Assess your team's data engineering knowledge, identify training needs, and ensure your engineers have the skills required for modern data infrastructure projects.

  • ✓ Team skill assessment
  • ✓ Training needs identification
  • ✓ Hiring validation

Join the Community

r/dataengineering • r/PostgreSQL • r/sql • r/devops

Data Stack Show • Data Engineering Podcast

Frequently Asked Questions

Our AI-powered grading system works invisibly in the background—it's there when you need it, but never gets in the way of the challenge. We use AI responsibly and smartly to keep learning challenging and fun. All questions and answers are expert-designed to ensure error-free learning. For objective questions, it checks your selection against the correct answer. For subjective questions, the AI provides subtle guidance when you need it—just enough help to keep you learning without taking away the fun of solving problems yourself. The challenge remains intact because you learn by pushing yourself a bit more, not by having answers handed to you.

Yes, the Data Engineering Challenge platform is completely free to use. You can practice as many questions as you want, access all features including AI-powered grading and progressive hints, and track your progress without any cost.

Our quizzes cover a comprehensive range of data engineering topics including SQL and databases, statistics and analytics (essential for data engineers), data modeling and ETL processes, data warehousing, big data technologies (Hadoop, Spark), data pipeline design, and data quality and testing. All questions are expert-designed to ensure accuracy and maintain the right level of challenge—ranging from foundational concepts to advanced scenarios that keep learning fun and engaging.

Each question comes with two progressive hints. The first hint provides a gentle nudge in the right direction, while the second hint offers more specific guidance. If you submit an incorrect answer, our invisible AI may provide a subtle suggestion to help you think through the problem differently—just enough to keep you moving forward without spoiling the challenge or fun. We use AI smartly to maintain the learning challenge while ensuring you get accurate guidance.

The platform uses an offline-first architecture, which means you can view questions and your previous answers even without an internet connection. However, submitting new answers and receiving AI-powered grading requires an active internet connection to communicate with our evaluation service.

Your progress is automatically saved locally in your browser. This includes your answers, grades, and quiz completion status. You can see your overall score, number of correct answers, and hints used. When you complete a quiz, you'll receive a comprehensive summary of your performance.

Objective questions are multiple-choice questions with predefined answer options. Subjective questions require you to write your own answer, which is then evaluated by our AI-powered grading system. Both types are designed to test different aspects of your data engineering knowledge and skills.

Yes, you can restart a quiz at any time. When you restart, all your previous answers and progress will be cleared, allowing you to start fresh. This is useful if you want to retake a quiz to improve your score or practice specific concepts again.

While LeetCode focuses on coding algorithms and data structures, the Data Engineering Challenge is AI-native LeetCode for data engineers. Our platform emphasizes SQL, database design, ETL processes, data warehousing, and pipeline architecture—skills essential for data engineers but not covered in traditional coding interview platforms. All questions are expert-designed to ensure error-free learning. We use AI responsibly and smartly—it works invisibly in the background, providing the right help at the right time to keep challenges fun while maintaining the learning difficulty. You learn by pushing yourself a bit more, not by having the challenge removed.

Unlike many platforms that only offer multiple-choice questions or require manual review, our platform provides AI-powered grading of subjective answers. This means you can explain concepts in your own words and receive instant feedback. All questions and answers are expert-designed to ensure error-free learning. We use AI responsibly and smartly—it works invisibly in the background to keep challenges fun while maintaining the right level of difficulty. Our progressive hint system helps you learn without giving away answers, and our offline-first architecture ensures you can practice anywhere. We focus specifically on practical data engineering scenarios that mirror real-world challenges you'll face in your career.

While ChatGPT and Google NotebookLM are excellent tools for learning, they lack the structured assessment and expert-designed questions that our platform provides. Our platform offers curated challenges designed by data engineering experts, ensuring error-free learning. We use AI responsibly and smartly—it works invisibly in the background to keep challenges fun while maintaining the learning difficulty. You get consistent feedback that helps you learn without taking away the challenge or fun, plus a clear way to track your progress over time. The key difference: you learn by pushing yourself a bit more, with expert-designed questions that ensure accuracy, and AI that helps when needed without making things too easy.

This is one of the most common questions in 2026! Here's why SQL skills are more valuable than ever:

  • AI needs your expertise: While AI can generate SQL, you need deep understanding to validate, debug, optimize, and ensure queries meet business requirements. AI output often needs refinement for production use.
  • Performance matters: AI doesn't always write efficient queries. Understanding SQL deeply helps you optimize for performance, cost, and scalability—critical in production systems.
  • Data modeling & architecture: SQL knowledge is essential for designing schemas, understanding relationships, and making architectural decisions that AI can't replace.
  • Critical thinking: Writing SQL trains your analytical thinking. You learn to break down complex problems and understand data flows—skills that transcend SQL itself.
  • Statistics & analysis: Our platform also covers statistics, which is essential for data engineers to understand data distributions, sampling, and analytical concepts that inform better data engineering decisions.

The bottom line: In 2026, the best data engineers use AI as a powerful tool, but their deep SQL, statistics, and data engineering knowledge makes them indispensable. AI amplifies your skills—it doesn't replace them.