Virtusa - Snowflake Data Engineer - Agentic Workflows

Role Overview :

We are looking for an experienced Snowflake Data Engineer with strong expertise in Snowflake, SQL, Python, dbt, and Snowflake CoCo (Cortex Code), along with hands-on experience building agentic workflows that automate the data engineering lifecycle.

Key Responsibilities :

- Design, develop, and maintain agentic data engineering workflows using Snowflake CoCo/Cortex Code.

- Build workflows that automate stages of the data engineering lifecycle, including discovery, impact analysis, development, testing, validation, and deployment.

- Integrate LLMs, Snowflake Cortex AI capabilities, agentic logic, and orchestration workflows into enterprise data engineering processes.

- Build Specification-Driven Development (SDD) capabilities using machine-readable specifications and instructions for data products.

- Work with Data Engineers and Architects to identify repetitive engineering activities and convert them into reusable agentic patterns and workflows.

- Develop and maintain high-quality Snowflake data pipelines, data models, transformations, and enterprise data products.

- Build and maintain dbt models, SQL stored procedures, and DataOps.Live orchestration workflows.

- Support automated engineering workflows covering data ingestion, transformation, testing, validation, and deployment.

- Apply enterprise data architecture patterns such as Bronze, Silver, and Gold layers to build scalable data products.

- Ensure data products are optimized for enterprise consumption, performance, reliability, and maintainability.

- Implement RAG-based workflows, tool integrations, and context-aware agent patterns where applicable.

- Work with Model Context Protocol (MCP) and related agent integration patterns to connect AI agents with enterprise tools and data sources.

- Ensure agentic workflows and generated engineering outputs comply with data governance, security, quality, and development standards.

- Monitor and improve automation quality, accuracy, reliability, and engineering efficiency.

- Collaborate with Data Engineering, Architecture, DevOps, Product, and business teams to drive adoption of AI-assisted engineering practices.

Required Skills & Experience :

- 7 - 16 years of experience in Data Engineering, Data Platform Engineering, or a closely related field.

- 7+ years of hands-on experience with Snowflake Data Engineering.

- Strong hands-on expertise in Snowflake SQL and Python.

- Strong experience with dbt, including model development, testing, deployment, and optimization.

- Hands-on experience with Snowflake CoCo / Cortex Code and agentic data engineering workflows.

- Strong understanding of LLM integration, AI/GenAI engineering, and Retrieval-Augmented Generation (RAG) concepts.

- Experience building or maintaining agentic workflows, AI agents, or orchestration frameworks.

- Hands-on understanding of MCP (Model Context Protocol) and agent-to-tool/data integrations.

- Strong knowledge of Snowflake Cortex AI capabilities and Cortex Skills.

- Strong experience with SQL-based data transformations, stored procedures, data pipelines, and data quality validation.

- Experience with DataOps.Live or similar data engineering orchestration and CI/CD platforms.

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

- Experience with data engineering lifecycle processes covering Discover, Build, Test, and Deploy.

- Strong understanding of data governance, quality, security, and development best practices.

- Strong analytical, problem-solving, communication, and cross-functional collaboration skills.