Data Engineering Mock Interview - Second Round

Join Sai Vineel, an experienced Data Engineering professional with over 8 years of experience, and Manoj for an exciting and informative Data Engineering mock interview session.

If you're preparing for a Data Engineering interview, this is the perfect opportunity to enhance your skills and increase your chances of success. The mock interview simulates a real-life scenario and provides valuable insights and guidance. The topics covered include discussion on SQL vs NoSQL, Git Practices, Deployment methodology in the Data Engineering etc.

It covered questions from Apache Spark, SQL, Airflow, File Formats, ETL pipelines, data modelling, database technologies, cloud platforms, and more. You'll get to see how professionals tackle technical questions and problem-solving challenges in a structured and efficient manner.

By watching this mock interview, you'll learn effective strategies to approach technical questions and problem-solving scenarios, gain familiarity with the data engineering interview process and format, enhance your communication skills and ability to articulate your thoughts clearly, identify areas of improvement, receive expert feedback on your performance, boost your confidence, and reduce nervousness for future interviews.

This mock interview suits all levels of experience, whether you're a fresh graduate, a career changer, or a seasoned professional looking to improve your interview skills. Don't miss out on this invaluable learning experience! Subscribe to our channel and hit the notification bell to be notified when the mock interview is released. Stay tuned for a deep dive into the world of data engineering.

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Chapters:

00:00 - Introduction
06:24 - Medalian Architecture
08:14 - Protobuf File Format
09:18 - How do you ensure Data Quality?
11:56 - Data Modeling Question
19:15 - Why do we need to Denormalize the data?
22:02 - Designing data Pipeline & various scenario-based question
29:29 - Key difference between LakeHouse and Data Lake
31:59 - What is SCD2? When it is useful?
33:44 - Project Deployment from one environment to another environment
34:31 - When you trigger your pipeline, how does it execute?
35:33 - Key consideration from SQL to NOSQL
37:27 - Challenges faced in Pyspark
38:45 - Day-to-day data engineering task
40:35 - How do you ensure the pipeline does not repeat a similar kind of failure?
42:43 - Best Practice for versioning control
44:44 - When to use RDBMS and when to use NoSQL?


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