Snowflake AI Engineer

Job Type

Full-time

Description

AI Snowflake Engineer

We are HALO! We connect people and brands to create unforgettable, meaningful, and lasting experiences that build brand engagement and loyalty for our over 60,000 clients globally, including over 100 of the Fortune 500. Our nearly 2,000 employees and 1,000 Account Executives located in 40+ sales offices across the United States are the reason HALO is #1 in our $25B industry.

HALO Branded Solutions is seeking a skilled and curious Snowflake AI Engineer to join our growing  Data & Analytics team. In this role, you will be at the forefront of how we unlock the value of our  enterprise data — building a robust Semantic Layer that brings structure and business context to  our data assets, and developing intelligent Cortex Agents that empower our teams to get instant,  trusted answers through natural language conversations. You will work closely with data engineers, business analysts, and stakeholders across the  organization to understand how our data is created and used, translate that understanding into a  well-governed semantic model, and bring it to life through Snowflake’s AI-native capabilities. This is  a high-impact, highly visible position for someone who loves both the craft of data engineering and  the challenge of making data accessible to everyone.

Responsibilities

Semantic Layer Development

• Partner with stakeholders and data owners across HALO to develop a deep understanding of our enterprise data domains — including merchandise, orders, programs, client accounts, and recognition data.

• Design and implement a comprehensive Semantic Layer within Snowflake, applying consistent business definitions, metrics, hierarchies, and context to our data assets.

• Define and maintain semantic models, logical data objects, and certified metrics that serve as the trusted foundation for analytics and AI use cases.

• Collaborate with the broader data team to ensure the Semantic Layer stays aligned with evolving data models, source systems, and business logic.

• Document semantic definitions, lineage, and business rules to support data literacy and governance across the organization.

Cortex Agent Development

• Design, build, and deploy Snowflake Cortex Agents that allow business users to interact with enterprise data through natural language queries.

• Develop and fine-tune agent logic, intent parsing, and response generation to ensure  accurate, reliable, and business-context-aware answers.

• Integrate Cortex Agents with the Semantic Layer to ground AI responses in governed, certified data.

• Establish feedback loops and monitoring to continuously improve agent performance, answer quality, and user trust.

• Work with end users and stakeholders to identify high-value agent use cases, iterate on  functionality, and drive adoption.

Platform & Collaboration

• Stay current with Snowflake’s evolving AI and data cloud capabilities, evaluating and championing new features relevant to our roadmap.

• Contribute to data engineering best practices, coding standards, and peer review within the team.

• Communicate technical concepts clearly to non-technical audiences, enabling business partners to understand and trust the data and AI tools you build.

• Support data governance initiatives by promoting consistent, well-documented, and auditable data practices.

Requirements

• 3+ years of experience working with Snowflake in a data engineering, analytics engineering, or AI/ML engineering capacity.
• Demonstrated experience designing and implementing semantic or logical data models (e.g.,  Snowflake Semantic Layer, dbt Semantic Layer, LookML, or equivalent).
• Hands-on experience with Snowflake Cortex features, including Cortex Analyst, Cortex  Search, or AI/ML functions.
• Strong SQL proficiency with deep knowledge of Snowflake-specific features (dynamic tables,  materialized views, streams, tasks, row access policies).
• Solid understanding of enterprise data concepts — dimensional modeling, data vault, or  medallion architecture patterns.
• Experience working in cross-functional environments, translating business requirements into  technical data solutions.
• Strong communication skills — able to articulate data concepts to both technical and non-technical stakeholders.

Preferred Experience

• Experience with LLM integration patterns, prompt engineering, or AI agent frameworks.
• Familiarity with dbt for data transformation and semantic …