Databases (Postgres, Oracle—CDC, bulk). APIs (REST, GraphQL). Files (CSV, JSON, Parquet on S3/GCS). Streaming (Kafka, Kinesis). SaaS (Salesforce, Stripe via Fivetran). Data lakes (Delta, Iceberg). Legacy (mainframe, FTP). Tailor to experience....
This hard-level General/Other question appears frequently in data engineering interviews at companies like Cognizant. While less common, it tests deeper understanding that distinguishes strong candidates.
This is a senior-level question that tests architectural thinking. Lead with the high-level design, then drill into specifics. Discuss trade-offs explicitly - there is rarely one correct answer. Show awareness of scale, fault tolerance, and operational complexity.
Databases (Postgres, Oracle—CDC, bulk). APIs (REST, GraphQL). Files (CSV, JSON, Parquet on S3/GCS). Streaming (Kafka, Kinesis). SaaS (Salesforce, Stripe via Fivetran). Data lakes (Delta, Iceberg). Legacy (mainframe, FTP). Tailor to experience. Show variety and patterns (CDC, pagination, idempotency).
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Analyze My Answer — FreeAccording to DataEngPrep.tech, this is one of the most frequently asked General/Other interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.