Role & responsibilities

Data and Knowledge Engineer

Prepares and pipelines enterprise data required for AI applications. Owns ingestion, transformation, metadata, quality controls, retrieval preparation, and data access patterns. Ensures source data used for grounding is trustworthy, governed, and fit for operational use. Supports structured and unstructured data flows needed for AI applications. Also manages data pipelines to purchased AI applications such as Sinequa Enterprise Search and other adjacent AI eco systems like ChatGPT and MS365 CoPilot, manages the knowledge assets used for grounding models, and supports the management of unstructured databases and repositories used for retrieval and grounding.

Data engineering, ETL/ELT, SQL, Python, data modeling, data quality, metadata/lineage, document processing, vectorization pipeline concepts, AWS data services, secure data access design, enterprise search/data integration, management of unstructured data stores and repositories.

📌 Data Engineer with AI Application exp (Ahmedabad)
🏢 Pyramid IT Consulting
📍 Ahmedabad