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Interview Questions Guides & Tutorials
Curated interview question banks with answers — SQL, Python, data science, Spark, Power BI, AWS, ADF and more.
Interview Questions articles
NLP Interview Questions for Data Scientists
NLP interview questions start with fundamentals that still decide most real text projects: how text becomes features, how to evaluate honestly and how to set a threshold. Six questions are answered on 5,574 real SMS messages, where duplicates, character n-grams and a 99% precision target all change the answer.
REST API Interview Questions and Answers
REST API questions test whether you understand HTTP itself: which methods are safe to retry, which status code means what, how clients page through data and avoid re-downloading it. Five questions are answered with a small working service over New York's 265 taxi zones, with every response shown.
Airflow Interview Questions for Data Engineers
Airflow interviews probe the behaviour that surprises teams in production. Five questions are answered by running a real Airflow 3 pipeline on household power data, including a validation failure that Airflow marked as a successful run, an empty data interval, and the documented fix for both.
Azure Interview Questions for Data Engineers
Azure data engineering interviews dig into storage: which tier to use, how folders really work, and how to grant access safely. This guide prices the tiers with Azure's live rates for Central India and runs the real Azure Storage SDK against Microsoft's Azurite emulator to show prefixes, overwrite protection and SAS.
BigQuery Interview Questions and Answers
BigQuery interviews mix SQL with cost: what a query will be billed, and how table design changes it. Seven questions are answered with GoogleSQL run locally on real New York taxi data and with Google's own documentation: column costs, LIMIT, approximate counts, QUALIFY, arrays, and partitioning with clustering.
Databricks Interview Questions and Answers
Most Databricks interview questions are really Delta Lake questions. Six are answered by building a real Delta table from daily bike-share data: what each write adds to the transaction log, time travel, a MERGE that rejects duplicate keys, schema enforcement, compacting 32 small files into one, and VACUUM.