30 Data Pipeline & Architecture Design questions are almost asked in every interviews, both at the fresher and experienced levels in FAANG companies.
𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫-𝐋𝐞𝐯𝐞𝐥 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝐃𝐞𝐬𝐢𝐠𝐧 1. Design a Data Pipeline to process logs from web servers. 2. Design a batch ETL pipeline to process e-commerce transactions. 3. Design a streaming data pipeline for real-time stock prices. 4. Design a solution to ingest and store sensor data from IoT devices. 5. Design a data ingestion pipeline for CSV/JSON files from S3 to Redshift. 6. Design a user clickstream data pipeline. 7. Design a pipeline to clean and aggregate marketing campaign data. 8. Design a daily job that syncs data from MySQL to BigQuery. 9. Design a basic data lake architecture. 10. Design a system that processes and analyzes ride-sharing trip data. 11. Design a data pipeline to detect fraud in payment transactions. 12. Design a system to track real-time delivery status in a food app. 13. Design an ETL pipeline for mobile app usage metrics. 14. Design a workflow to migrate data between two cloud environments. 15. Design a pipeline to monitor and alert on data quality issues.
𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞𝐝-𝐋𝐞𝐯𝐞𝐥 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝐃𝐞𝐬𝐢𝐠𝐧 16. Design a real-time analytics platform like Uber's Michelangelo. 17. Design a scalable log aggregation and querying system like ELK. 18. Design a CDC (Change Data Capture) system using Debezium and Kafka. 19. Design a batch + streaming hybrid architecture (Lambda/Kappa). 20. Design a warehouse architecture supporting SCD. 21. Design a distributed ETL pipeline using Spark or PySpark. 22. Design a time-series data warehouse for monitoring and IoT. 23. Design an event-driven architecture for order processing using Kafka. 24. Design a metadata management system like Apache Atlas. 25. Design a data catalog and lineage tracker. 26. Design a self-healing pipeline with retry, alert, and failover. 27. Design a real-time dashboard using Kafka + Flink + Druid. 28. Design a scalable system for A/B testing analysis. 29. Design a data pipeline to feed a recommendation engine. 30. Design a multi-tenant data platform for product analytics at scale.
Start implementing to stand out in your next Data Engineer role.
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30 Data Pipeline & Architecture Design questions are almost asked in every interviews, both at the fresher and experienced levels in FAANG companies.
𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫-𝐋𝐞𝐯𝐞𝐥 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝐃𝐞𝐬𝐢𝐠𝐧
1. Design a Data Pipeline to process logs from web servers.
2. Design a batch ETL pipeline to process e-commerce transactions.
3. Design a streaming data pipeline for real-time stock prices.
4. Design a solution to ingest and store sensor data from IoT devices.
5. Design a data ingestion pipeline for CSV/JSON files from S3 to Redshift.
6. Design a user clickstream data pipeline.
7. Design a pipeline to clean and aggregate marketing campaign data.
8. Design a daily job that syncs data from MySQL to BigQuery.
9. Design a basic data lake architecture.
10. Design a system that processes and analyzes ride-sharing trip data.
11. Design a data pipeline to detect fraud in payment transactions.
12. Design a system to track real-time delivery status in a food app.
13. Design an ETL pipeline for mobile app usage metrics.
14. Design a workflow to migrate data between two cloud environments.
15. Design a pipeline to monitor and alert on data quality issues.
𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞𝐝-𝐋𝐞𝐯𝐞𝐥 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝐃𝐞𝐬𝐢𝐠𝐧
16. Design a real-time analytics platform like Uber's Michelangelo.
17. Design a scalable log aggregation and querying system like ELK.
18. Design a CDC (Change Data Capture) system using Debezium and Kafka.
19. Design a batch + streaming hybrid architecture (Lambda/Kappa).
20. Design a warehouse architecture supporting SCD.
21. Design a distributed ETL pipeline using Spark or PySpark.
22. Design a time-series data warehouse for monitoring and IoT.
23. Design an event-driven architecture for order processing using Kafka.
24. Design a metadata management system like Apache Atlas.
25. Design a data catalog and lineage tracker.
26. Design a self-healing pipeline with retry, alert, and failover.
27. Design a real-time dashboard using Kafka + Flink + Druid.
28. Design a scalable system for A/B testing analysis.
29. Design a data pipeline to feed a recommendation engine.
30. Design a multi-tenant data platform for product analytics at scale.
Start implementing to stand out in your next Data Engineer role.
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