Master SQL, Data Warehousing, Big Data, Cloud, Python, and System Design with 101 Real Interview Questions
Are you preparing for a Data Engineering interview with top product-based companies, MNCs, or startups?
This course is your one-stop preparation guide — designed to help you crack interviews at FANG/MANG and beyond.
What you’ll learn
- Confidently answer 101 of the most frequently asked Data Engineering interview questions across SQL, Big Data, Cloud, and System Design..
- Master advanced SQL concepts such as joins, window functions, CTEs, indexing, and query optimization through real-world examples..
- Understand Data Warehousing, ETL, and Data Modeling techniques (OLTP vs OLAP, Fact vs Dimension, Star vs Snowflake schema, Slowly Changing Dimensions, CDC)..
- Gain hands-on clarity in Big Data & Cloud technologies like Hadoop, Spark, Kafka, Snowflake, AWS, Azure, and GCP by exploring practical use cases..
- Develop strong problem-solving and communication skills to tackle both technical and behavioral interview rounds with confidence..
- Learn system design patterns for data pipelines (batch vs streaming, lakehouse architecture, real-time processing with Kafka + Spark)..
Course Content
- Introduction to the Course –> 2 lectures • 4min.
- SQL & Database Essentials (20 Questions) –> 20 lectures • 29min.
- Section 3: Data Warehousing & ETL (15 Questions) –> 15 lectures • 26min.
- Section 4: Big Data Ecosystem (15 Questions) –> 15 lectures • 26min.
- Section 5: Cloud Data Engineering (15 Questions) –> 15 lectures • 28min.
- Section 6: Data Modeling & Architecture (12 Questions) –> 12 lectures • 20min.
- Section 7: Python & Data Engineering Coding (10 Questions) –> 9 lectures • 17min.
- Section 8: System Design for Data Engineers (8 Questions) –> 8 lectures • 15min.
- Section 9: Behavioral & Scenario Questions –> 7 lectures • 7min.
- Section 10: Mock Interview Simulation –> 3 lectures • 4min.
Requirements
Are you preparing for a Data Engineering interview with top product-based companies, MNCs, or startups?
This course is your one-stop preparation guide — designed to help you crack interviews at FANG/MANG and beyond.
Inside, you’ll find:
-> 101 Most Asked Interview Questions — covering SQL, ETL, Data Warehousing, Big Data (Spark/Hadoop), Cloud Data Engineering (AWS/GCP/Azure), Python, Data Modeling, and System Design.
-> Detailed Explanations with Real Examples — each question comes with slides + voiceover-style breakdowns to make concepts crystal clear.
-> Scenario-Based & Behavioral Questions — learn how to answer “pipeline failure” or “wrong data in production” confidently.
-> Mock Interview Simulations — practice with end-to-end rounds combining technical + behavioral questions.
=> What makes this course different?
Unlike theory-heavy courses, this one focuses on real-world, interview-style answers.
Each answer is structured into:
- Slide 1: Question + Context (why it’s asked)
- Slide 2: Key Points to Cover (must-have points)
- Voiceover Script: A natural, human-style explanation with real project scenarios
By the end of this course, you’ll be able to:
- Answer any SQL, Big Data, or Cloud interview question with confidence
- Handle system design and architecture questions for data platforms
- Communicate behavioral answers like a pro
- Approach real interviews with a structured preparation strategy
=> Who is this course for?
- Aspiring Data Engineers preparing for their first job interviews
- Working professionals aiming to switch into FANG/MANG or Tier-1 companies
- Software Developers, BI Engineers, and Analysts transitioning into Data Engineering
- Students or graduates looking to master interview skills before placements
=> Why take this course?
Because interviews don’t test just knowledge — they test how you explain it.
This course will teach you what to say, how to say it, and how to stand out from other candidates.
=> Ready to land your dream job in Data Engineering?
Enroll now and start your journey with Top 101 Data Engineering Interview Questions!
Please Note: “This course contains the use of artificial intelligence.”