Developed a Pinecone Vector Database ingestion feature for the datahub-project/datahub repository, focusing on seamless integration of external vector data sources. Leveraging Python and expertise in API integration, the work enabled automated extraction of metadata from Pinecone indexes and namespaces, enriching ingested records with contextual information. The implementation included schema inference from vector metadata, allowing for dynamic schema generation and improving the utility of downstream analytics and search. By establishing an end-to-end ingestion pipeline, the developer enhanced data fidelity and streamlined metadata management, demonstrating depth in data ingestion workflows and schema automation within the context of modern vector database technologies.