AWS Data Engineering Mock (3-5 Years Experience)

This mock interview evaluates a candidate’s ability to build efficient and scalable data pipelines using AWS. Key focus areas include:

• AWS Services: Glue, S3, Redshift, Lambda, Step Functions, Kinesis, DynamoDB.
• ETL & Data Processing: Data ingestion, transformation, and storage strategies.
• Big Data & Streaming: Batch vs. real-time processing using Spark, Kinesis, Redshift Streaming.
• Performance Optimization: Query tuning, partitioning, and cost-effective solutions.
• Security & Governance: IAM roles, encryption, and fine-grained access control.
• Troubleshooting & Debugging: Identifying bottlenecks, optimizing Glue & Redshift.
• Coding & Scripting: SQL queries, PySpark transformations, and AWS automation with Python.

Candidates will tackle real-world AWS Data Engineering scenarios, demonstrating problem-solving skills and best practices.