Join EY's AI & Data practice as a Senior Data Engineer specializing in Snowflake. You'll have the opportunity to architect and deliver AI-enabled data platforms that drive analytics, operational decisions, and responsible AI for clients. This role offers a chance to build a unique career leveraging global scale and inclusive culture.

This position focuses on end-to-end ownership of data products and technical workstreams, integrating strong engineering principles with native AI capabilities on Snowflake. Emphasis is placed on delivering business value, ensuring security, and maintaining reliable production operations.

Design and construct secure, high-performance data products on Snowflake, utilizing features like warehouses, dynamic tables, Snowpark, and Snowpipe. Implement robust data ingestion, transformation, orchestration, and performance optimization using SQL, Python, Snowpark, and dbt.

Develop scalable batch and streaming data solutions, defining appropriate data models, processing patterns, and quality controls. Troubleshoot complex performance, reliability, and cost issues, establishing reusable engineering patterns and guiding code reviews.

Translate business requirements into well-documented, tested data products with clear ownership and service-level expectations. Leverage Snowflake Cortex capabilities, including Cortex AI functions and Cortex Agents, for governed native AI solutions. Design AI-ready data products and implement production patterns for retrieval, semantic search, and reliable operation.

Possess advanced SQL and Python skills, with required Snowpark and PySpark experience. Demonstrate expertise in data modeling, query profiling, warehouse sizing, and resource monitors. Proficiency in CI/CD, Git, and deployment automation is essential.

Experience implementing RAG, semantic search, agent workflows, or LLM evaluation is highly advantageous. Strong analytical problem-solving abilities, excellent written and verbal communication skills, and a consulting mindset focused on measurable client outcomes are critical.

Requires 5-8 years of relevant data engineering, analytics engineering, or platform engineering experience. A Bachelor’s or Master’s degree in a related field or equivalent practical experience is necessary. Experience with modern data modeling, distributed processing, and cloud data security is mandatory. SnowPro certification is preferred.