How to Build a Real-Time DynamoDB to S3 Analytics Pipeline with Apache Iceberg

Introduction Data is at the core of almost every modern application, but it is rarely stored in a way that makes it immediately useful. Data engineering focuses on moving data from source systems, shaping it, and storing it so it can be analyzed and queried later. As applications scale and data volumes grow, building reliable and flexible data pipelines becomes an essential part of the system. On AWS, this is usually done using managed services that work well together-such as DynamoDB for storage, Kinesis for streaming, S3 for durable data lakes, and Glue and Athena for cataloging and querying. These services reduce operational effort, but building a dependable pipeline still requires careful handling of streaming behavior and schema changes. In one of our recent projects, we needed to build a near real-time data pipeline that streamed data from DynamoDB into S3 (S3 Tables). The goal was to make this data available in real time for analytics while keeping the system scalable and future