Data Transformation and Loading Questions

Focuses on the extract transform load and extract load transform approaches for ingesting transforming and loading data. Candidates should understand three core stages: extract which is acquiring data from sources such as application programming interfaces databases logs and message queues; transform which is cleaning validating reshaping aggregating and enriching data to meet downstream requirements; and load which is writing processed data to targets such as analytic databases data warehouses data lakes or reporting systems. Topics include the differences between extract transform load and extract load transform, incremental loads versus full refresh, scheduling and orchestration best practices, tooling and frameworks used for transformation and orchestration, idempotency and deduplication strategies, error handling and retry semantics, data quality checks end to end validation recovery and integration with business intelligence and analytics consumers. Interview focus is on concrete transformation logic pipeline orchestration and validation strategies and on choosing the right pattern and tooling for given constraints.