Questions that have appeared at databricks for a engineering (Case Study) interview.

1. Big Data Architecture

Question: Can you describe a big data architecture that you have designed or worked with? What were the key components and how did they interact?

Question: What considerations do you take into account when designing a big data architecture?

Question: How do you handle data latency in big data architectures?

2. Distributed Systems

Question: Can you explain the trade-offs between consistency, availability, and partition tolerance in a distributed system?

Question: How would you design a distributed system to handle a large volume of real-time data?

Question: What strategies can be implemented to recover from failure in distributed systems?

3. Data Processing

Question: How do you ensure data quality during processing?

Question: What strategies would you use to optimize the performance of a large-scale data processing job?

Question: How do you handle data transformation failures during processing?

4. Data Security

Question: How would you ensure data security in a distributed processing system?

Question: What are the major threats to data security in a big data environment and how would you mitigate them?

Question: What encryption methods would you recommend for securing data at rest and in transit?

5. Cloud Computing

Question: How have you leveraged cloud computing in your previous projects?

Question: What are the benefits and challenges of migrating a big data architecture to the cloud?

Question: How would you design a cost-effective cloud-based big data architecture?

6. Data Lake

Question: Can you describe how to design and implement a data lake?

Question: What are the advantages and disadvantages of using a data lake architecture?

Question: How would you ensure data quality in a data lake environment?

7. Data Governance

Question: How have you implemented data governance in your previous projects?

Question: What are the key factors to consider when developing a data governance strategy?

Question: How do you handle data privacy and regulatory requirements in a big data environment?

8. Machine Learning

Question: How have you used machine learning in your previous projects?

Question: Can you describe a situation where machine learning improved the efficiency of a process or system?

Question: What are the challenges when incorporating machine learning into a big data architecture?

9. Scalability

Question: How have you designed a system to be scalable?

Question: Can you describe a situation where you had to scale a system to accommodate increased data volume?

Question: What are the key factors to consider when planning for scalability in a big data architecture?

10. Performance Optimization

Question: How do you identify bottlenecks in a big data architecture?

Question: What strategies have you used to optimize the performance of a big data architecture?

Question: Can you provide an example where your performance optimization efforts had a significant impact?