Agentic AI Data Engineer – Snowflake & Cortex AI
Virtusa
Primary Focus:
- Development, orchestration, and maintenance of the agentic framework that automates the engineering lifecycle.
- Technical execution and delivery of the Data Engineering lifecycle (Discover, Build, Test, Deploy).
- 6+ Years Experience Snowflake Data Engineer with CoCo exp
- Develop and refine agentic workflows using the Snowflake CoCo (CoCo) harness. Integrate LLMs, Cortex AI models, and orchestration logic to automate discovery, impact analysis, build, and testing stages.
- Build "Specification Driven Development" (SDD) capabilities, creating machine-readable instructions for data products.
- Collaborate with Data Engineers to convert manual engineering tasks into autonomous agentic patterns.
- Drive technical execution for data product delivery and datasets optimized for enterprise consumption.
- Oversee core engineering layer components, including SQL Stored Procedures, DBT models, and DataOps.Live.
- Maintain code quality and minimize defects while ensuring full alignment with EDO governance standards Contribute to automated engineering lifecycles—covering ingestion through deployment—via platform-agnostic frameworks.
- AI/GenAI Engineering: Deep experience with Cortex Skills, LLM integration, and Retrieval-Augmented Generation (RAG) concepts.
- Agentic Frameworks: Proficiency in building and maintaining agentic workflows (e.g., CoCo CLI, Model Context Protocol).
- Foundational Knowledge: Solid background in data engineering (SQL, Python) to bridge the gap between AI capabilities and data platform requirements.
- Core Engineering Competencies: Advanced technical mastery of SQL, DBT models, and DataOps.Live (DOL) orchestration.
- Platform Expertise: Comprehensive proficiency across the Snowflake ecosystem and its integrated service offerings.
- Data Product Lifecycle: Strategic command of multi-tier architectures (Bronze, Silver, Gold) and the management of enterprise-grade data products.
710years