Have you worked on Apache Iceberg and handled AWS Glue tables?
💡 Model Answer
Yes, I have extensive experience with Apache Iceberg and AWS Glue. In my previous role, I used Iceberg to manage large analytical tables in a data lake on S3. Iceberg’s schema evolution, partitioning, and snapshot isolation features allowed us to perform time‑travel queries and rollbacks without rewriting the entire dataset. I integrated Iceberg with Glue by creating Glue Data Catalog tables that point to Iceberg metadata. This enabled Glue crawlers to discover Iceberg tables and Spark jobs to read/write them using the Iceberg API. For incremental processing, I leveraged Glue ETL jobs that read the latest Iceberg snapshots and write new partitions to S3, then updated the Glue catalog. I also used Glue’s job bookmarking to avoid reprocessing data. Additionally, I set up Glue workflows to orchestrate daily ingestion from source systems, transform data with Spark, and write to Iceberg tables, ensuring ACID compliance and efficient query performance on Athena and Redshift Spectrum.
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