Virtusa - Snowflake DBT Cortex AI Engineer

We are looking for a Snowflake DBT Cortex AI Engineer to design, develop, and maintain agentic engineering frameworks that automate the data engineering lifecycle. The role combines AI/GenAI engineering, Snowflake, DBT, data engineering, and agentic workflow orchestration, with a strong focus on automating data product discovery, impact analysis, development, testing, and deployment.

The ideal candidate will have strong hands-on experience with Snowflake, SQL, Python, DBT, Cortex AI, LLM integration, RAG, and agentic frameworks, along with a solid understanding of enterprise data product architectures.

Key Responsibilities :

- Design, develop, and maintain agentic workflows that automate the data engineering lifecycle.

- Build and enhance agentic solutions using the Snowflake CoCo harness/CLI and related orchestration frameworks.

- Integrate LLMs, Snowflake Cortex AI models, and orchestration logic to automate discovery, impact analysis, development, testing, and deployment activities.

- Develop Specification-Driven Development (SDD) capabilities using machine-readable instructions for data products and engineering workflows.

- Collaborate with Data Engineers to identify manual engineering activities and convert them into scalable, autonomous agentic workflows.

- Support the end-to-end data engineering lifecycle, including Discover, Build, Test, and Deploy.

- Develop and maintain enterprise-grade data products and datasets optimized for downstream consumption.

- Work with SQL Stored Procedures, DBT models, and DataOps.Live (DOL) as part of the core engineering layer.

- Contribute to automated data engineering frameworks covering ingestion through deployment.

- Ensure agentic solutions and engineering components meet quality, reliability, security, and governance standards.

- Troubleshoot and resolve issues across AI workflows, data pipelines, DBT models, SQL, and orchestration components.

- Collaborate with Data Engineering, AI/ML, platform, and governance teams to drive adoption of autonomous engineering practices.

- Design solutions that are scalable, maintainable, and aligned with enterprise data architecture and EDO governance standards.

Requirements :

- 4 - 9 years of experience in Data Engineering, AI/GenAI Engineering, or related technology roles, with strong hands-on engineering experience.

- Strong experience with Snowflake and its ecosystem, including Cortex AI and integrated platform services.

- Hands-on experience with advanced SQL, Python, and DBT.

- Strong understanding of Data Engineering lifecycle, including data ingestion, transformation, testing, deployment, and orchestration.

- Experience developing or maintaining agentic AI workflows and AI-driven automation frameworks.

- Strong understanding of LLM integration, Cortex AI models, and Retrieval-Augmented Generation (RAG) concepts.

- Experience with agentic frameworks or technologies such as CoCo CLI and Model Context Protocol (MCP).

- Hands-on experience with DBT models, SQL Stored Procedures, and DataOps.Live (DOL).

- Strong understanding of enterprise data product architectures, including Bronze, Silver, and Gold layers.

- Experience building and managing enterprise-grade data products and datasets.

- Ability to translate manual data engineering processes into automated and agentic engineering patterns.

- Strong understanding of data quality, governance, reliability, and engineering best practices.

- Good collaboration and communication skills, with the ability to work closely with Data Engineering and AI/ML teams.