Data Engineer Scenario based interview !!
Scenario 1:
Interviewer: Can you design a data warehouse for an e-commerce company with 10 million customers and 1 million orders per day?
Candidate: Yes, I would design a data warehouse using Azure Synapse Analytics or Amazon Redshift, with a star schema architecture and appropriate indexing and partitioning to handle the large volume of data.
Scenario 2:
Interviewer: How would you optimize a slow-performing query that takes 10 minutes to execute?
Candidate: I would analyze the query plan, identify performance bottlenecks, and apply optimization techniques like indexing, caching, and query rewriting to reduce execution time to less than 1 minute.
Scenario 3:
Interviewer: Can you integrate data from 5 different sources, including APIs, databases, and files, into a single data platform?
Candidate: Yes, I would use Azure Data Factory or Apache NiFi to integrate the data sources, transform and cleanse the data as needed, and load it into a unified data platform like Azure Data Lake Storage or Amazon S3.
Scenario 4:
Interviewer: How would you ensure data security and compliance with regulations like GDPR and HIPAA?
Candidate: I would implement encryption, access controls, data masking, and auditing to ensure data security and compliance, and regularly monitor and update security measures to ensure ongoing compliance.
Scenario 5:
Interviewer: Can you design a real-time data streaming platform to process 1 million events per second?
Candidate: Yes, I would design a platform using Apache Kafka or Amazon Kinesis, with appropriate clustering, partitioning, and replication to handle the high volume of data, and ensure real-time processing and analytics.
Some additional questions and figures:
- Interviewer: How do you handle data quality issues in a data warehouse?
Candidate: I would implement data validation, data cleansing, and data quality checks to ensure data accuracy and completeness, and regularly monitor and improve data quality.
- Interviewer: Can you optimize data storage costs for a large data lake?
Candidate: Yes, I would use data compression, data deduplication, and tiered storage to reduce storage costs by up to 50%.
- Interviewer: How do you ensure data governance and compliance across multiple teams and departments?
Candidate: I would establish clear data governance policies, procedures, and standards, and regularly monitor and enforce compliance across teams and departments.
