Can you load data into JSON as a silver layer, then transform it and load it into Redshift?

Yes. In a typical bronze‑silver‑gold architecture, the bronze layer stores raw, unprocessed data (often in Parquet or JSON). The silver layer is where we perform cleaning, deduplication, and schema enforcement. Loading raw JSON into the silver layer can be done using AWS Glue or Spark, where we parse the JSON, apply transformations (e.g., flatten nested structures, cast types, filter out bad records), and write the cleaned data back to S3 in a structured format like Parquet. From the silver layer, we can then run ETL jobs that aggregate or enrich the data and finally load the results into Redshift using the COPY command. This approach keeps the raw data intact for auditability while providing a clean, query‑optimized dataset in Redshift for analytics.