Big Data Mock Interview | Data Engineering Interview | First Round of Interview

Data Engineering Mock Interview

Join PadmaPriya Uppala, an experienced Data Engineering professional with over 6 years of experience, and Amrita a Senior Data Engineer 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 interview scenario and provides valuable insights and guidance. The topics covered include #apachespark SQL, 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 is suitable for all levels of experience, whether you're a fresh graduate, a career changer, or a seasoned professional looking to brush up on 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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🔅 To book a Mock interview - https://topmate.io/ankur_ranjan/15155

🔅 LinkedIn -   / thebigdatashow  

🔅 Instagram -   / ranjan_anku  

🔅 PadmaPriya Uppala(Interviewer) 's LinkedIn profile -   / padmapriya-uppala  

🔅 Amrita (Interviewee)'s LinkedIn profile -

Chapters:

00:00 - Introduction
05:10 - Role in the project
06:22 - Handling streaming job failure
07:52 - Handling the Lost data in a real time project
08:24 - What is the watermark in Spark Structure Streaming? In which scenario one should use a watermark?
10:16 - Difference between event time & processing time
10:41 - Kind of transformation used in the project
12:40 - Spark Scenario Based Question
16:48 - Reason behind choosing Avro File format over other
17:18 - Reason behind choosing Iceberg
18:00 - Architecture of Iceberg
19:00 - Difference between RDD, DataFrame & DataSet. And do we need to choose which?
20:30 - Spark Optimization Technique
22:35 - What is DAG in Airflow? What is a job, Stage & task in Apache Spark?
24:45 - At what scenario we should choose Kafka?
26:37 - SQL Questions
40:31 - DSA Question
50:45 - Interviewee Feedback




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