How would you build an ETL pipeline to read JSON files that are irregularly dropped into storage, transform the data, and match the schema?

Question

Accepted Answer

Design an ETL pipeline to handle irregularly timed JSON file uploads for data transformation and schema matching.

Use a cloud storage service (e.g., AWS S3) to store incoming JSON files.
Implement a file watcher or event-driven architecture (e.g., AWS Lambda) to trigger processing when new files arrive.
Utilize a data processing framework (e.g., Apache Spark or Apache Beam) to read and transform the JSON data.
Define a schema using a tool like Apache Avro or JSON Schema to ensure consistency across different JSON files.
Perform data validation and cleansing to handle missing or malformed data.
Load the transformed data into a data warehouse (e.g., Amazon Redshift, Google BigQuery) for analysis.

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