Round 1: Technical (1 Hr)

✅ Tell me about yourself and any recent projects you have been a part of.

✅ Questions related to your projects.

✅ How would you connect multiple tables from different AWS databases (e.g., RDS, Redshift) using a single connection in AWS Glue?

✅ What are the different types of triggers in AWS Glue or AWS Step Functions?

✅ How do you deploy code from DEV to QA and PROD environments using AWS services?

✅ How do you create a CI/CD pipeline for deployment in AWS using CodePipeline, CodeCommit, and CodeBuild?

✅ What types of transformations have you performed in your projects using AWS Glue or other services?

✅ How can you replace spaces in column names with underscores in source files using AWS Glue and S3?

✅ What is SCD Type 2, and how can you implement it in AWS using Glue or Redshift?

✅ What are the differences between AWS S3 and AWS Redshift in terms of data storage and usage?

✅ How do you read data from S3 using Amazon Redshift Spectrum or Athena?

✅ Write a Python function to merge two sorted lists into one sorted list.

✅ Write an SQL Query to fetch 2nd highest salary department wise and differe approaches to do it.

Round 2: Technical (30 Mins)

✅ How do you create a view in AWS Glue or Amazon Redshift?

✅ Write a DDL command in Amazon Redshift to create a table.

✅ What AWS Glue activities have you used in your project?

✅ Are you familiar with AWS S3 and IAM security? How do you secure access to data in S3?

✅ What are the different authentication methods available in AWS Glue for accessing S3 or RDS?

✅ How many team members are there in your team and what's your role in the team?

✅ What are your skillsets, roles, and responsibilities in your current data engineering project, especially around Spark and AWS?

✅ How would you design a pipeline to ingest, transform, and load (ETL) large datasets from S3 into Amazon Redshift using Spark?

✅ How would you implement data versioning in a Spark-based pipeline, ensuring that data can be tracked across versions?

✅ Questions related to Spark Optimizations like what are they and when to use them

Round 3: HR

✅ Discussion around my experience and projects, some resume-based questions.

✅ What are you expecting in your next job role?

✅ Package discussion