AI Data Solutions Architect (Chicago)

The AI Data Solutions Architect is a senior technical role within the AI Center of Excellence, responsible for designing and governing the data architecture that underpins all AI and machine learning initiatives across Camping World Holdings. This individual will own the end-to-end data strategy for AI projects - determining where data should reside, how it flows between systems, and how it is structured to maximize value for AI workloads. They will maintain a comprehensive data lineage and usage inventory, ensuring the organization has clear visibility into where data is sourced, transformed, stored, and consumed. Key Responsibilities AI Data Architecture & Design

• Define and maintain the enterprise data architecture for all AI and machine learning projects, including data lake, warehouse, and feature store strategies.

• Design data models, schemas, and pipelines optimized for AI/ML consumption across Snowflake, BigQuery, Postgres, and supporting platforms.

• Establish standards for data ingestion, transformation, storage, and retrieval that support real-time and batch AI workloads.

• Architect integration patterns that connect structured and unstructured data sources (Snowflake, Salesforce, SharePoint, PDFs, APIs) into unified, AI-ready datasets. Data Lineage, Governance & Inventory

• Build and maintain a comprehensive data catalog and lineage map that documents where every critical data asset lives, how it is used, and which AI models depend on it.

• Partner with Data Engineering and Analytics teams to ensure data quality, consistency, and compliance across all AI data pipelines.

• Implement metadata management practices and tooling to enable self-service discovery and impact analysis.

• Define data classification, access controls, and retention policies for AI-specific datasets in alignment with security and regulatory requirements. AI Project Delivery & Collaboration

• Serve as the embedded data architect across all AI Center of Excellence projects, ensuring each initiative has a sound data foundation from design through deployment.

• Collaborate with AI/ML engineers, agent developers, and platform teams to translate business requirements into data architecture decisions.

• Evaluate and recommend data technologies, connectors, and integration tools that accelerate AI delivery (e.g., vector databases, RAG pipelines, embedding stores).

• Support the buildout of the enterprise data lake initiative, consolidating disparate data sources for AI and analytics workloads. Strategic Planning & Standards

• Develop and maintain data architecture standards, reference architectures, and design patterns tailored for AI use cases.

• Create and present architecture proposals, data flow diagrams, and technical documentation to both technical and executive audiences.

• Stay current on emerging data technologies, cloud-native data services, and AI infrastructure patterns; advise leadership on adoption opportunities.

• Contribute to the AI Center of Excellence’s technology standards and roadmap for data infrastructure

Pay Rate: $75-100/hour

8+ years of experience in data architecture, data engineering, or enterprise data management.

• 3+ years of hands-on experience designing data solutions for AI/ML workloads.
• Deep expertise with cloud data platforms, particularly Snowflake, Google BigQuery, or equivalent.

• Strong understanding of data modeling (dimensional, graph, document), ETL/ELT pipelines, and data integration patterns.

• Experience with data governance frameworks, data cataloging tools, and lineage tracking.

• Familiarity with AI/ML data requirements including feature engineering, vector embeddings, retrieval augmented generation (RAG), and unstructured data processing.

• Proficiency in SQL; working knowledge of Python or similar scripting languages.

• Excellent communication skills with the ability to translate complex data concepts for non-technical stakeholders.

• Bachelor’s degree in Computer Science, Data Science, Information Systems, or related field.

Nice to Have Skills & Experience

Experience with Snowflake’s advanced features (Snowpark, Cortex, data sharing, dynamic tables).

• Hands-on experience with GCP services (Vertex AI, Cloud Storage, Pub/Sub, Dataflow).
• Familiarity with knowledge graph technologies, semantic layers, or ontology design for AI applications.
• Experience with enterprise data lake or data mesh architectures.
• Background in retail, automotive, or RV/dealership industry data environments.
• Relevant certifications (e.g., Snowflake SnowPro, GCP Professional Data Engineer, AWS Data Analytics).
• Experience with MCP (Model Context Protocol) or similar AI-to-data integration frameworks

Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.