#W2 Role
*Position Overview* We are seeking an AI Data Engineer to build and maintain scalable data solutions that support AI and analytics across investment and enterprise data. This role will focus on developing AI-ready data assets, implementing Snowflake Cortex capabilities, and enabling agents, copilots, and retrieval-augmented generation (RAG) solutions. *Key Responsibilities* - Build and maintain scalable data pipelines in Snowflake for the ingestion, transformation, and curation of investment and enterprise data. - Prepare unstructured data for AI use cases through chunking, tagging, metadata enrichment, and vectorization. - Implement Snowflake Cortex Search to support retrieval and discovery across structured and unstructured data assets. - Develop semantic views and models for Snowflake Cortex Analyst to enable natural-language access to governed data. - Design and maintain AI-ready data assets, including vectorized datasets, metadata models, and retrieval frameworks that support agents, copilots, and RAG solutions. - Develop data engineering solutions using Snowflake Cortex, SQL, Python, and modern cloud tooling. - Ensure data quality, performance, security, and observability across pipelines and data products. - Partner with business stakeholders and AI engineering teams to translate complex investment data requirements into reusable, governed data products. - Support initiatives such as CII, Risk AI, Trade Agent, and other enterprise AI platforms. *Required Qualifications* - Hands-on experience building data pipelines and analytics solutions in Snowflake. - Strong proficiency in SQL and Python for data ingestion, transformation, and processing. - Experience with Snowflake Cortex, including Cortex Search and Cortex Analyst. - Experience processing unstructured data, including chunking, tagging, metadata management, and vectorization. - Understanding of semantic modeling, retrieval frameworks, and RAG architectures. - Experience applying data quality, governance, security, monitoring, and performance optimization practices. - Ability to collaborate with business and technical teams to deliver reusable data products. *Preferred Qualifications* - Experience working with investment, financial services, or enterprise data. - Experience supporting AI agents, copilots, or enterprise AI platforms. - Familiarity with cloud-based data orchestration and modern data engineering tools.