Summary

The article discusses the architecture and challenges of LinkedIn's job ingestion system, which processes millions of job postings daily from diverse sources. It highlights the importance of reliability, scalability, and extensibility in handling heterogeneous job data feeds. The system employs a modular, event-driven pipeline that includes job intake and processing stages, utilizing various methods for data extraction and transformation. The article emphasizes the need for robust security protocols and maintaining data quality to ensure a trustworthy job catalog for users.

Data Problems Addressed