Harvest Group
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Harvest Group is a trusted integrated commerce agency that specializes in serving CPG suppliers looking to grow their business at Walmart, Target, Amazon, Kroger, Sam’s Club, Costco, and Harris Teeter. Harvest Group offers a connected commerce solution leading their clients with account management, digital content management, retail media management, and replenishment services. Established in 2006, our multi‑functional team of retail experts leverages first‑class systems and technologies to support our clients along every step of the retail journey.
Description Harvest Group is searching for a Senior AI Data Architect to work with business and technology stakeholders to deliver an AI‑driven data experience by overlaying large language models on top of our data warehouse. This role is primarily focused on discovering, designing, and building the semantic and technical layers that enable secure, accurate, conversational access to our data. The Senior Data Architect will coordinate closely with other technology teams to create an enterprise‑ready, production‑grade conversational intelligence capability. You’ll be exposed to varied datasets from many providers and will make that data safely available through an LLM‑powered interface. To do this, you’ll need to grasp how the business operates, how the data is useful, how it’s structured, and how it relates across domains—then translate that knowledge into a scalable architecture that LLMs can understand and use. Join our team to learn the intricacies of the consumer packaged goods (CPG) retail industry and lead data democratization via AI and cloud solutions to grow our clients’ businesses.
Our approach to servicing our employees is grounded in our values. To deliver excellence for our Harvest Group employees, we do require that this role is based in Rogers (AR) or Cincinnati (OH). If you are applying but do not currently reside in one of these markets, please note that relocation will not be covered by Harvest Group.
Responsibilities
Review and evolve current data structures—models, schemas, and naming/metadata conventions—in our data warehouse to make them more LLM/AI‑ready (clear semantics, consistent business definitions, performant patterns, and governed access).
Design, implement, and maintain the semantic and metadata layers that sit between LLMs and our data warehouse to enable governed, conversational access to data.
Build and operationalize unstructured contextual data pipelines (e.g., documents, PDFs, presentations, images, logs, tickets), including ingestion, parsing/OCR, chunking, metadata extraction, embedding generation, indexing, and integration into the AI/RAG platform.
Architect secure RAG (retrieval‑augmented generation) patterns, including query planning, grounding, and context assembly from our data warehouse and related systems.
Stand up rapid proofs of concept and experiments; iterate quickly to de‑risk approaches, then harden winning patterns into enterprise‑ready solutions.
Partner with business end‑users to understand questions and decisions, then translate them into schemas, policies, and conversational intents the system can reliably support.
Create clear technical documentation and enablement materials for internal users and support teams.
Requirements
5+ years in a data architecture role designing analytic data models and platform components (cloud preferred).
5+ years in data engineering across ingestion, transformation, modeling, and performance optimization.
1+ years building LLM‑powered applications or services (e.g., ChatGPT, Azure OpenAI, or comparable) including retrieval, function/tool use, or agents.
Strong proficiency with Snowflake (data modeling, performance, governance, role‑based security).
Proficient in SQL and a programming language such as Python for data and LLM orchestration.
Demonstrated ability to communicate with both technical and non‑technical partners and to lead through influence.
Proven track record of shipping systems from prototype to production with attention to reliability, cost, and maintainability.
Preferred Qualifications
Experience with Snowflake AI capabilities (e.g., vector search, UDFs/UDTFs, external functions) and/or Snowflake Intelligence/Cortex concepts.
Hands‑on use of LLM frameworks and evaluation tooling; familiarity with prompt engineering and function/tool calling.
Experience building or managing a semantic layer (e.g., dbt Semantic Layer, Looker semantic model, AtScale, Cube, or similar) to mediate between users/LLMs and data.
Practical knowledge of vector databases and embeddings (e.g., pgvector, Pinecone, FAISS) and when to prefer native warehouse approaches.
Experience with orchestration and CI/CD for data/AI workloads (dbt, Airflow/Dagster, git‑based workflows).
Background in data governance and security for AI use cases (masking, row/column‑level security, lineage, auditing).
Working in an Agile Scrum framework with rapid, iterative delivery.
CPG retail industry experience and familiarity with retailer data ecosystems.
We encourage all interested candidates to apply.
Harvest Group is an equal opportunity employer that does not discriminate on the basis of race, creed, color, religion, age, marital status, familial status, national origin, ancestry, disability or handicap, sexual orientation, gender identity or expression, veteran status, and any other characteristic protected by applicable federal, state, or local laws.
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Harvest Group is a trusted integrated commerce agency that specializes in serving CPG suppliers looking to grow their business at Walmart, Target, Amazon, Kroger, Sam’s Club, Costco, and Harris Teeter. Harvest Group offers a connected commerce solution leading their clients with account management, digital content management, retail media management, and replenishment services. Established in 2006, our multi‑functional team of retail experts leverages first‑class systems and technologies to support our clients along every step of the retail journey.
Description Harvest Group is searching for a Senior AI Data Architect to work with business and technology stakeholders to deliver an AI‑driven data experience by overlaying large language models on top of our data warehouse. This role is primarily focused on discovering, designing, and building the semantic and technical layers that enable secure, accurate, conversational access to our data. The Senior Data Architect will coordinate closely with other technology teams to create an enterprise‑ready, production‑grade conversational intelligence capability. You’ll be exposed to varied datasets from many providers and will make that data safely available through an LLM‑powered interface. To do this, you’ll need to grasp how the business operates, how the data is useful, how it’s structured, and how it relates across domains—then translate that knowledge into a scalable architecture that LLMs can understand and use. Join our team to learn the intricacies of the consumer packaged goods (CPG) retail industry and lead data democratization via AI and cloud solutions to grow our clients’ businesses.
Our approach to servicing our employees is grounded in our values. To deliver excellence for our Harvest Group employees, we do require that this role is based in Rogers (AR) or Cincinnati (OH). If you are applying but do not currently reside in one of these markets, please note that relocation will not be covered by Harvest Group.
Responsibilities
Review and evolve current data structures—models, schemas, and naming/metadata conventions—in our data warehouse to make them more LLM/AI‑ready (clear semantics, consistent business definitions, performant patterns, and governed access).
Design, implement, and maintain the semantic and metadata layers that sit between LLMs and our data warehouse to enable governed, conversational access to data.
Build and operationalize unstructured contextual data pipelines (e.g., documents, PDFs, presentations, images, logs, tickets), including ingestion, parsing/OCR, chunking, metadata extraction, embedding generation, indexing, and integration into the AI/RAG platform.
Architect secure RAG (retrieval‑augmented generation) patterns, including query planning, grounding, and context assembly from our data warehouse and related systems.
Stand up rapid proofs of concept and experiments; iterate quickly to de‑risk approaches, then harden winning patterns into enterprise‑ready solutions.
Partner with business end‑users to understand questions and decisions, then translate them into schemas, policies, and conversational intents the system can reliably support.
Create clear technical documentation and enablement materials for internal users and support teams.
Requirements
5+ years in a data architecture role designing analytic data models and platform components (cloud preferred).
5+ years in data engineering across ingestion, transformation, modeling, and performance optimization.
1+ years building LLM‑powered applications or services (e.g., ChatGPT, Azure OpenAI, or comparable) including retrieval, function/tool use, or agents.
Strong proficiency with Snowflake (data modeling, performance, governance, role‑based security).
Proficient in SQL and a programming language such as Python for data and LLM orchestration.
Demonstrated ability to communicate with both technical and non‑technical partners and to lead through influence.
Proven track record of shipping systems from prototype to production with attention to reliability, cost, and maintainability.
Preferred Qualifications
Experience with Snowflake AI capabilities (e.g., vector search, UDFs/UDTFs, external functions) and/or Snowflake Intelligence/Cortex concepts.
Hands‑on use of LLM frameworks and evaluation tooling; familiarity with prompt engineering and function/tool calling.
Experience building or managing a semantic layer (e.g., dbt Semantic Layer, Looker semantic model, AtScale, Cube, or similar) to mediate between users/LLMs and data.
Practical knowledge of vector databases and embeddings (e.g., pgvector, Pinecone, FAISS) and when to prefer native warehouse approaches.
Experience with orchestration and CI/CD for data/AI workloads (dbt, Airflow/Dagster, git‑based workflows).
Background in data governance and security for AI use cases (masking, row/column‑level security, lineage, auditing).
Working in an Agile Scrum framework with rapid, iterative delivery.
CPG retail industry experience and familiarity with retailer data ecosystems.
We encourage all interested candidates to apply.
Harvest Group is an equal opportunity employer that does not discriminate on the basis of race, creed, color, religion, age, marital status, familial status, national origin, ancestry, disability or handicap, sexual orientation, gender identity or expression, veteran status, and any other characteristic protected by applicable federal, state, or local laws.
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