Senior Data Analytics Engineer – Snowflake | Onsite-Chicago, IL | Direct Hire | No Sponsorship

We are seeking a Senior Snowflake Data Engineer – Analytics & AI to design, build, and evolve a modern data platform centered around Snowflake. This role will be responsible for transforming data from source systems into trusted, analytics-ready, and AI-ready data products that power business intelligence, advanced analytics, and agentic AI applications.

The ideal candidate has strong hands-on experience with Snowflake, SQL, and Python, along with a solid understanding of modern data architecture and data transformation patterns. You will help establish and extend a medallion architecture, building robust Silver and Gold data layers while creating the data structures and semantic capabilities required to make enterprise data accessible to both traditional BI tools and AI systems.

The overall data flow will span:

Source Systems → Openflow → Snowflake → BI / AI Applications

This role will also focus heavily on preparing data for the next generation of AI applications. You will develop AI-ready data products, semantic views, and data structures that enable AI agents and large language models (LLMs) to discover, understand, query, and reason over enterprise data. This includes leveraging Snowflake's AI capabilities to bridge natural-language requests and enterprise data, enabling users and agents to translate NLP into accurate SQL queries and interact with data through general-purpose LLMs.

Key Responsibilities

Data Engineering & Medallion Architecture

• Design and implement scalable data pipelines and data models within Snowflake.
• Build and maintain Silver and Gold layers within a medallion architecture.
• Transform and enrich data flowing from source systems through Openflow into Snowflake.
• Develop reliable, reusable data models that support analytics, reporting, and downstream applications.
• Establish data quality, consistency, governance, and performance standards across curated data layers.
• Optimize Snowflake workloads, SQL queries, data models, and pipelines for scalability and performance.

Snowflake Application Development

• Build external applications and data solutions that leverage Snowflake as a core application and data platform.
• Develop Snowflake-centric solutions that expose trusted enterprise data to downstream applications and users.
• Leverage Snowflake capabilities for data transformation, application development, AI, and analytics.
• Integrate Snowflake with upstream source systems and downstream BI, AI, and application technologies.

Business Intelligence & Analytics Enablement

• Develop Gold-layer data products optimized for business intelligence and analytics.
• Create data structures that can be consumed by BI platforms such as Sigma.
• Partner with analytics and business teams to translate business requirements into scalable data models.
• Ensure curated datasets are intuitive, performant, and appropriately structured for self-service analytics.

AI-Ready & Agentic Data

• Design and build AI-ready data products that can be consumed by AI agents and LLM-powered applications.
• Structure and transform enterprise data so that agents can reliably discover, interpret, and use it.
• Develop data assets that provide appropriate context, relationships, metadata, and business meaning for AI systems.
• Build and maintain semantic views and semantic data models that enable AI systems to understand enterprise data.
• Leverage Snowflake AI capabilities to enable natural-language interaction with enterprise data.
• Help bridge general-purpose LLMs with enterprise data by providing the appropriate semantic and query layer.
• Enable natural-language requests to be translated into accurate and governed SQL queries.
• Work with emerging agentic architectures to support automated data discovery, transformation, querying, and analysis.