Udemy - Top 101 Data Engineering Interview Questions
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- TypeTutorials
- LanguageEnglish
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- Last checkedSep. 30th '25
- Date uploadedSep. 26th '25
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Top 101 Data Engineering Interview Questions
https://WebToolTip.com
Published 9/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 53m | Size: 1.31 GB
Master SQL, Data Warehousing, Big Data, Cloud, Python, and System Design with 101 Real Interview Questions
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).
Requirements
No prior experience as a Data Engineer is strictly required — this course is designed for both beginners and professionals preparing for interviews.
Basic knowledge of SQL (SELECT, JOIN, GROUP BY) will be helpful but not mandatory.
Familiarity with at least one programming language (Python, Java, or Scala) is a plus but not required.
Curiosity to learn and a desire to crack Data Engineering interviews at top companies.
A laptop/PC with internet connection to follow along with examples and practice queries.
Files:
[ WebToolTip.com ] Udemy - Top 101 Data Engineering Interview Questions- Get Bonus Downloads Here.url (0.2 KB) ~Get Your Files Here ! 1 - Introduction to the Course
- 1 -How to use this course (Slides + Voiceover transcripts + Practice approach).mp4 (11.6 MB)
- 2 -Why interviews focus on problem-solving, not just theory.mp4 (23.6 MB)
- 1 -Round 1 SQL + Behavioral Mix.mp4 (4.0 MB)
- 2 -Round 2 Data Modeling + System Design.mp4 (5.0 MB)
- 3 -Round 3 Cloud + End-to-End Case Study.mp4 (38.7 MB)
- 1 -Q1. What is the difference between OLTP and OLAP systems.mp4 (8.5 MB)
- 10 -Q10. Explain the difference between DELETE, TRUNCATE, and DROP.mp4 (12.4 MB)
- 11 -Q11. What are ACID properties in databases, and why are they important.mp4 (12.6 MB)
- 12 -Q12. Explain the difference between WHERE vs HAVING clauses.mp4 (8.2 MB)
- 13 -Q13. What is a Stored Procedure vs a Function in SQL.mp4 (10.1 MB)
- 14 -Q14. What are Views in SQL, and when would you use them.mp4 (11.4 MB)
- 15 -Q15. Explain Aggregate Functions vs Analytic Functions.mp4 (14.1 MB)
- 16 -Q16. How do you handle NULL values in SQL queries.mp4 (11.7 MB)
- 17 -Q17. Explain the difference between INNER JOIN vs FULL OUTER JOIN with examples.mp4 (9.7 MB)
- 18 -Q18. What is a Self Join and when is it useful.mp4 (1.4 MB)
- 19 -Q19. Second highest salary from an Employee table.mp4 (14.4 MB)
- 2 -Q2. Explain INNER JOIN vs LEFT JOIN with examples.mp4 (6.0 MB)
- 20 -Q20. concept of Transactions and how to implement them in SQL.mp4 (12.0 MB)
- 3 -Q3. What are Window Functions in SQL and why are they useful.mp4 (7.4 MB)
- 4 -Q4. How would you optimize a slow SQL query.mp4 (12.0 MB)
- 5 -Q5. Explain Primary Key, Foreign Key, and Unique Key differences.mp4 (8.3 MB)
- 6 -Q6. (CTE) and how is it different from a Subquery.mp4 (9.9 MB)
- 7 -Q7. Explain UNION vs UNION ALL with examples.mp4 (7.5 MB)
- 8 -Q8. What is the difference between Normalization and Denormalization.mp4 (10.6 MB)
- 9 -Q9. What are Indexes in SQL and what types exist (Clustered vs Non-Clustered).mp4 (15.1 MB)
- 1 -Q1. What is the difference between Data Warehouse, Data Lake, and Data Lakehouse.mp4 (16.3 MB)
- 10 -Q10. How do you design a surrogate key vs natural key in a warehouse.mp4 (11.2 MB)
- 11 -Q11. What are Orchestration tools (Airflow, ADF, Glue) and how do they differ.mp4 (11.2 MB)
- 12 -Q12. How do you handle late arriving dimensions in ETL.mp4 (13.6 MB)
- 14 -Q14. How do you handle CDC (Change Data Capture) in ETL pipelines.mp4 (12.8 MB)
- 15 -Q15. What are some common ETL performance optimization techniques.mp4 (14.5 MB)
- 2 -Q2. Explain Star Schema vs Snowflake Schema with examples.mp4 (11.2 MB)
- 3 -Q3. What are Fact Tables and Dimension Tables Give real-world examples.mp4 (10.0 MB)
- 4 -Q4. What are Slowly Changing Dimensions (SCDs) Explain different types (Type 1,.mp4 (16.6 MB)
- 5 -Q5. What is the difference between ETL and ELT processes.mp4 (15.0 MB)
- 6 -Q6. How do you handle schema changes in ETL pipelines.mp4 (19.6 MB)
- 7 -Q7. What are Incremental Load vs Full Load strategies in data pipelines.mp4 (8.5 MB)
- 8 -Q8. What are Data Quality checks in ETL, and why are they important.mp4 (16.1 MB)
- 9 -Q9. What is Data Partitioning and how does it help performance in DWH.mp4 (16.6 MB)
- 1 -Q1. What is the difference between (HDFS) and traditional file systems.mp4 (14.1 MB)
- 10 -Q10. How does Checkpointing and Caching work in Spark, and why are they importan.mp4 (13.4 MB)
- 11 -Q11. What is the difference between Batch Processing and Stream Processing.mp4 (10.4 MB)
- 12 -Q12. Explain Spark Structured Streaming and how it handles real-time data.mp4 (24.6 MB)
- 13 -Q13. What are Partitions in Spark, and how do they affect performance.mp4 (12.7 MB)
- 14 -Q14. What are some common Spark optimization techniques.mp4 (11.7 MB)
- 15 -How do you handle schema evolution and semi-structured data (JSON, Avro).mp4 (13.7 MB)
- 2 -Q2. Explain MapReduce and why it was important in the Hadoop ecosystem.mp4 (19.9 MB)
- 3 -Q3. What are the differences between RDD, DF, and Dataset in Apache Spark.mp4 (14.2 MB)
- 4 -Q4. Explain lazy evaluation in Spark and why it’s useful.mp4 (12.9 MB)
- 5 -Q5. What is a Shuffle in Spark, and how can you optimize shuffle operations.mp4 (23.2 MB)
- 6 -Q6. Compare Spark SQL vs Hive – when would you use one over the other.mp4 (18.2 MB)
- 7 -Q7. Explain the role of YARN vs Kubernetes in running big data jobs.mp4 (11.3 MB)
- 8 -Q8. What are Broadcast Joins in Spark, and when should you use them.mp4 (13.4 MB)
- 9 -Q9. What are Wide vs Narrow transformations in Spark.mp4 (20.1 MB)
- 1 -Q1.What is the difference between Data Lake and a Data Warehouse in the cloud.mp4 (18.0 MB)
- 10 -Q10. What are cross-region and cross-cloud data replication strategies.mp4 (14.7 MB)
- 11 -Q11. How do you implement data governance and compliance in cloud pipelines.mp4 (14.3 MB)
- 12 -Q12. What are managed streaming services.mp4 (12.3 MB)
- 13 -Q13. How does CDC (Change Data Capture) work in cloud-native tools.mp4 (11.5 MB)
- 14 -Q14. Explain Lakehouse architectures in the cloud.mp4 (12.8 MB)
- 15 -Q15. How do you monitor, log, and troubleshoot cloud data pipelines effectively.mp4 (14.3 MB)
- 2 -Q2. Compare AWS Glue, (ADF), and GCP Dataflow – when would you use each.mp4 (14.1 MB)
- 3 -Q3. Explain Serverless vs Cluster-based data processing in cloud platforms.mp4 (13.4 MB)
- 4 -Q4. What are best practices for designing data pipelines in the cloud.mp4 (13.4 MB)
- 5 -Q5. How do you implement data partitioning and clustering in cloud warehouses.mp4 (15.3 MB)
- 6 -Q6. What is auto-scaling, and how does it benefit cloud data pipelines.mp4 (12.1 MB)
- 7 -Q7. Compare Snowflake vs BigQuery vs Redshift – strengths and weaknesses.mp4 (15.6 MB)
- 8 -Q8. How does cost optimization work in cloud data engineering.mp4 (12.5 MB)
- 9 -Q9. Explain IAM best practices for securing cloud data pipelines.mp4 (12.6 MB)
- 1 -Q1. What is Data Vault modeling, and how does it compare to KimballInmon.mp4 (13.7 MB)
- 10 -Q10. What is a multi-tenant data warehouse.mp4 (11.3 MB)
- 11 -Q11. How would you design a hybrid architecture combining batch and streaming.mp4 (1.8 MB)
- 12 -Q12. What are best practices for designing metada
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