Senior Data Architect Interview Questions

78 senior data architect interview questions shared by candidates

1. Explain your career experience. 2. Explain architect of your last project. 3. Have you worked on migration projects? 4. Explain different types of data models? 5. What is difference between snowflake vs star schema? 6. Which data modeler tool you have worked? Tell about that? 7. What is reverse engineering? 8. Tell approach if have to add new dimension in existing data warehouse? 9. Explain challenges faced in migrating data warehouse from one DMBS to another. 10. Have you used any cloud technology? 11. What are different types of S3 storages in AWS? 12. Explain different types of SCD?
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Senior Data Architect

Interviewed at Infosys

3.6
Jul 16, 2024

1. Explain your career experience. 2. Explain architect of your last project. 3. Have you worked on migration projects? 4. Explain different types of data models? 5. What is difference between snowflake vs star schema? 6. Which data modeler tool you have worked? Tell about that? 7. What is reverse engineering? 8. Tell approach if have to add new dimension in existing data warehouse? 9. Explain challenges faced in migrating data warehouse from one DMBS to another. 10. Have you used any cloud technology? 11. What are different types of S3 storages in AWS? 12. Explain different types of SCD?

Explain the key components of Apache Spark’s architecture. What are Spark Executors and Spark Driver? How do they communicate? Can you describe the difference between a DataFrame and an RDD in Spark? What are the main functions of the Spark Catalyst Optimizer? How does Spark handle fault tolerance? Explain the concept of lazy evaluation in Spark. Why is it beneficial?
avatar

Senior Data Architect

Interviewed at Tiger Analytics

4
Nov 8, 2024

Explain the key components of Apache Spark’s architecture. What are Spark Executors and Spark Driver? How do they communicate? Can you describe the difference between a DataFrame and an RDD in Spark? What are the main functions of the Spark Catalyst Optimizer? How does Spark handle fault tolerance? Explain the concept of lazy evaluation in Spark. Why is it beneficial?

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