TCS Data Engineer Interview Experience | Snowflake & SQL Questions | #vitechtalks#sqlinterview #snow

Planning to join TCS as a Data Engineer? In this video, I share the real interview experience of one of my students who recently interviewed for a Snowflake + Python Data Engineering role at TCS. You’ll learn: Join this channel to get access to perks: https://www.youtube.com/channel/UCOCmIxlnxT4NICdOR1E36vQ/join Technical questions on Snowflake, Python, and SQL ETL & Data Pipeline design scenarios Behavioral and project-based questions Tips to prepare for TCS and similar IT services companies If you’re aiming for TCS or Big 4 roles, this video will give you practical insights and preparation strategies. The video covers various questions related to Data Engineering, focusing on Snowflake, SQL, and general data concepts. Here are the main questions asked: Difference between Snowpipe and COPY INTO using tasks (2:21) How to set up event notifications for Snowpipe (3:00) Why use Snowpipe instead of scheduled COPY INTO tasks for batch processing (4:06) Is there a way to instantly get source data into Snowflake without delay? (6:16) Different ways to ingest data into Snowflake (7:24) Can a table schema be automatically defined from a file with many columns (e.g., thousands)? (8:59) How to recover a table if it was accidentally replaced with a different structure using CREATE OR REPLACE TABLE (11:00) SQL query to calculate sum of scores and average age based on class and subject, while showing all original columns (12:53) Limitations of using materialized views in Snowflake (13:51) Scenarios for creating a materialized view (14:32) Can a materialized view be created by joining data from two tables? (15:20) Is a materialized view suitable for frequently changing transactional data? (16:12) How are materialized views refreshed? (17:02) Is materialized view serverless, or does it require a warehouse for refreshing? (17:22) What happens if the assigned warehouse for a materialized view is suspended? Will the data be correct? (18:11) How to work with a huge volume of data for analysis to get nearly accurate results with less volume (21:44) Difference between TABLE SAMPLE and LIMIT clauses in SQL (23:20) Difference between CTE (Common Table Expression) and Temporary Table (24:18) Why use CTE if temporary tables can serve a similar purpose? (25:22) Does a temporary table store data in a remote disk/cloud? (26:07) #TCSInterview #TCSDataEngineer #SnowflakeInterview #SnowflakeMockInterview #SnowflakeRealTimeInterview #SnowflakeInterviewQuestions #PythonDataEngineering #TCSJobs #TCSCareers #DataEngineerInterview #SnowflakeArchitecture #SnowflakeETL #SnowflakeSQL #SnowflakePython #BigDataInterview #ETLPipeline #SnowflakeStreams #SnowflakeTasks #SnowflakeTimeTravel #SnowflakeCloning #SnowflakeCDC #PwC #DataEngineer #Snowflake #Python #Big4 #DataEngineering #ETL #SQLInterview #TechCareers #Snowflake #SnowflakeDataWarehouse #SnowflakeCloud #SnowflakeArchitecture #SnowflakeETL #SnowflakeSQL #SnowflakeTutorial #SnowflakeTraining #SnowflakeInterview #SnowflakeJobs #SnowflakeDeveloper #SnowflakeEngineer #SnowflakeDataEngineer #SnowflakePerformance #SnowflakeOptimization #SnowflakeFeatures #SnowflakeStreams #SnowflakeTasks #SnowflakeTimeTravel #SnowflakeCloning #SnowflakeCDC #SnowflakeDataSharing #SnowflakeSecurity #SnowflakeIntegration #SnowflakePython #SnowflakeWithPython #SnowflakePipeline #SnowflakeETLPipeline #SnowflakeBigData #SnowflakeAnalytics #SnowflakeDataModeling #SnowflakeSchema #SnowflakeWarehouse #SnowflakeVirtualWarehouse #SnowflakeStorageCompute #SnowflakeSemiStructuredData #SnowflakeJSON #SnowflakeVariant #SnowflakeMaterializedView #SnowflakeStage #SnowflakeSnowpipe #SnowflakeDataLoading #SnowflakeBestPractices #SnowflakeTips #SnowflakeQueryOptimization #SnowflakePerformanceTuning #SnowflakeCostOptimization #SnowflakeCloudComputing #SnowflakeDataPlatform #SnowflakeDataCloud #SnowflakeCertification #SnowflakeLearning #SnowflakeCareer #SnowflakeInterview #SnowflakeMockInterview #SnowflakeRealTimeInterview #SnowflakeInterviewQuestions #SnowflakeInterviewPreparation #SnowflakeInterviewTips #SnowflakeInterviewGuide #SnowflakeInterviewExperience #SnowflakeInterviewScenarios #SnowflakeInterviewPractice #SnowflakeInterviewSkills #SnowflakeInterviewCoding #SnowflakeInterviewSQL #SnowflakeInterviewPython #SnowflakeInterviewETL #SnowflakeInterviewDataEngineer #SnowflakeInterviewBig4 #SnowflakeInterviewPwC #SnowflakeInterviewPrep #SnowflakeInterviewSuccess