Real questions from top companies · hard
Explain BigQuery Architecture.
Explain Native vs. External Tables.
Articulate the architectural decisions, scalability trade-offs, and cost implications of designing an AWS data platform. How would you justify glue vs. EMR, Redshift vs. Athena, and when would each choice become cost-prohibitive at scale?
Explain the architectural rationale for using LeftAntiJoin vs. NOT IN vs. NOT EXISTS in a distributed context. When does LeftAntiJoin become a performance or scalability bottleneck, and how do broadcast vs. shuffle joins affect cost?
Explain the architectural trade-offs when optimizing a query on 100M+ rows: indexing vs. partitioning vs. materialized views. When does each approach become cost-prohibitive or operationally burdensome, and how do you quantify impact?
Explain bloom filters in Spark: how they reduce I/O and when they introduce false positives that hurt performance. What are the scalability and cost implications of enabling dynamic partition pruning and bloom filter pushdown at petabyte scale?
Design a star schema for retail analytics (e.g., Adidas). Explain the dimensional modeling choices, SCD strategy, and how you would scale this schema for global multi-currency, multi-region deployments. What are the refresh and storage cost implications?
Explain peer code review and team lead review.
Explain the Medallion Architecture (Bronze, Silver, Gold).
Explain the differences between OLTP and OLAP databases and their relevance in Adidas's operations.
Explain the purpose of windowing and triggering in streaming data pipelines.
Explain the use of Amazon Athena for serverless querying.
Features of NoSQL Databases
Given a CSV file with raw customer transactions, design an ETL pipeline that cleans data, aggregates total sales by region and product, and loads into target table
How can you automate data insertion into BigQuery using Python?
How did you manage a situation where you lacked knowledge for a task?
How do you design a scalable and fault-tolerant data warehouse on a cloud platform?
How do you handle situations where you disagree with feedback from others?
How does AQE optimize join operations dynamically?
How does it differ from static partition pruning?
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