Based on your resume, can you explain a project where you performed data ingestion using Glue, S3, Step Functions, and API Gateway?

In a recent project, I built a real‑time analytics pipeline for a SaaS product. API Gateway exposed a REST endpoint that received user activity logs in JSON. A Lambda function, triggered by API Gateway, validated the payload and wrote it to an S3 bucket in a raw folder. Step Functions orchestrated the workflow: after the Lambda write, a Glue crawler ran to update the Data Catalog with the new schema. A Glue ETL job then transformed the raw logs, enriched them with user profile data from DynamoDB, and wrote the cleaned data to a processed S3 folder. Finally, Athena queries on the processed data fed into a BI dashboard. This architecture leveraged Glue for automated schema discovery and ETL, Step Functions for orchestration, API Gateway for secure ingestion, and S3 for durable storage. Monitoring was handled via CloudWatch logs and metrics, and the entire pipeline was cost‑effective because it used serverless components with pay‑as‑you‑go pricing.