Big Data Mock Interview | Data Engineering Interview | First Round of Interview
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Data Engineering Mock InterviewJoin PadmaPriya
Data Engineering Mock Interview
Join PadmaPriya Uppala, an experienced Data Engineering professional with over 6 years of experience, and Akash 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.
Subscribe now and be the first to watch the Data Engineering Mock Interview with PadmaPriya & Akash.
🔅 To book a Mock interview - https://topmate.io/ankur_ranjan/15155
🔅 LinkedIn - LinkedIn: thebigdatashow
🔅 Instagram - Instagram: ranjan_anku
🔅 PadmaPriya Uppala(Interviewer) 's LinkedIn profile - LinkedIn: padmapriya-uppala
🔅 Akash Patel (Interviewee)'s LinkedIn profile - LinkedIn: akash-patel-37158a107
Chapters:
00:00 - Introduction & Project Discussion
06:03 - Reason behind choosing the parquet file format
07:41 - How does a parquet format help when compared to any row-based file format?
09:10 - When to choose DataLake and not a simple database or DataWarehouse?
11:34 - Data management strategies while ingesting and storing the parquet files in the data lake?
12:59 - Issues around writing complex transformations & their resolution
18:27 - Lazy Evaluation
21:46 - Different modes in Spark & when to use what
22:45 - Why we have been asked to avoid the use of the User Defined function(UDF)?
23:48 - What is Adaptive Query Execution(AQE)? And how does it help us?
25:35 - What is the scenario when you faced a Small file problem and how did you try to solve it?
26:55 - Design E2E data Pipeline and what are the things one should take care of in terms of different aspects such as quality, Governance or other data aspects?
33:29 - SQL Question
37:18 - What is idempotency? And in which scenario we should really take care?
39:33 - What is the use case of out-of-memory exception with Spark and how did you encounter it & how did you solve it?
41:44 - What is executor Memory in Spark and how to tune it with configuration and make it better in terms of execution?
44:52 - What is Sort Merge Bucket (SMB) Join and in which scenario do we tend to use it and how it will help us in the job execution?
46:06 - Project Challenges
46:59 - DSA Question
50:36 - While designing any pipeline have you ever discussed scalability or failure handling or any such consideration?
#dataengineering #interview #interviewquestions #bigdata #mockinterview #siliconvalley #usa
Join PadmaPriya Uppala, an experienced Data Engineering professional with over 6 years of experience, and Akash 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.
Subscribe now and be the first to watch the Data Engineering Mock Interview with PadmaPriya & Akash.
🔅 To book a Mock interview - https://topmate.io/ankur_ranjan/15155
🔅 LinkedIn - LinkedIn: thebigdatashow
🔅 Instagram - Instagram: ranjan_anku
🔅 PadmaPriya Uppala(Interviewer) 's LinkedIn profile - LinkedIn: padmapriya-uppala
🔅 Akash Patel (Interviewee)'s LinkedIn profile - LinkedIn: akash-patel-37158a107
Chapters:
00:00 - Introduction & Project Discussion
06:03 - Reason behind choosing the parquet file format
07:41 - How does a parquet format help when compared to any row-based file format?
09:10 - When to choose DataLake and not a simple database or DataWarehouse?
11:34 - Data management strategies while ingesting and storing the parquet files in the data lake?
12:59 - Issues around writing complex transformations & their resolution
18:27 - Lazy Evaluation
21:46 - Different modes in Spark & when to use what
22:45 - Why we have been asked to avoid the use of the User Defined function(UDF)?
23:48 - What is Adaptive Query Execution(AQE)? And how does it help us?
25:35 - What is the scenario when you faced a Small file problem and how did you try to solve it?
26:55 - Design E2E data Pipeline and what are the things one should take care of in terms of different aspects such as quality, Governance or other data aspects?
33:29 - SQL Question
37:18 - What is idempotency? And in which scenario we should really take care?
39:33 - What is the use case of out-of-memory exception with Spark and how did you encounter it & how did you solve it?
41:44 - What is executor Memory in Spark and how to tune it with configuration and make it better in terms of execution?
44:52 - What is Sort Merge Bucket (SMB) Join and in which scenario do we tend to use it and how it will help us in the job execution?
46:06 - Project Challenges
46:59 - DSA Question
50:36 - While designing any pipeline have you ever discussed scalability or failure handling or any such consideration?
#dataengineering #interview #interviewquestions #bigdata #mockinterview #siliconvalley #usa
5 ماه پیش
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