Job Description Insight Global is seeking a Senior Snowflake/Data consultant to support a large health insurance client of ours.

Key Responsibilities:

•  Design and implement unified data pipelines in Snowflake that combine structured tables, semi-structured data (JSON/Parquet), and large collections of documents (PDF, DOCX, text).
•  Build agentic document analytics workflows: large-scale document ingestion, text extraction, cleaning, chunking, embeddings, vector stores, and efficient retrieval for analytic queries.
•  Implement Natural Language Query (NLQ) interfaces that translate user text prompts into analytic queries or retrieval flows and return explainable results.
•  Integrate Snowflake with LLMs (OpenAI or equivalent) for tasks such as summarization, question-answering, classification, and code-generation—using External Functions, Snowpark, and/or secure API patterns.
•  Create performant retrieval-augmented generation (RAG) architectures that leverage Snowflake-stored embeddings and external or internal vector indexes as appropriate.
•  Author Snowpark/Python/SQL transformations, Streams & Tasks, and job orchestration to enable near-real-time and batch analytical workloads.
•  Implement data modeling and governance patterns within

Snowflake:

schemas, role-based access control, masking, lineage, and metadata to support analytics and compliance.

•  Partner with product, ML/AI, BI, and engineering teams to translate business requirements into robust production-ready solutions.
•  Build monitoring, observability, and cost controls for compute, storage, and API usage related to document analytics and LLM integration.
•  Produce technical documentation, runbooks, and clear explanations of model/LLM behavior and limitations to non-technical stakeholders.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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Insight Global's Workforce Privacy Policy:

https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements

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Statistical Analysis:

Proficiency in statistical methods and software, such as Python, to analyze data.

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Data Visualization:

Ability to create compelling visualizations using tools like Tableau, Power BI, and other cloud technologies.

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Database Management:

Knowledge of SQL and NoSQL databases for efficient data storage and retrieval.

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Programming:

Strong programming skills, particularly in languages such as Python, Java, and C++.

•  Design and implement unified data pipelines in Snowflake that combine structured tables, semi-structured data (JSON/Parquet), and large collections of documents (PDF, DOCX, text).
•  Build agentic document analytics workflows: large-scale document ingestion, text extraction, cleaning, chunking, embeddings, vector stores, and efficient retrieval for analytic queries.
•  Implement Natural Language Query (NLQ) interfaces that translate user text prompts into analytic queries or retrieval flows and return explainable results.
•  Integrate Snowflake with LLMs (OpenAI or equivalent) for tasks such as summarization, question-answering, classification, and code-generation—using External Functions, Snowpark, and/or secure API patterns.
•  Create performant retrieval-augmented generation (RAG) architectures that leverage Snowflake-stored embeddings and external or internal vector indexes as appropriate.
•  Author Snowpark/Python/SQL transformations, Streams & Tasks, and job orchestration to enable near-real-time and batch analytical workloads.
•  Implement data modeling and governance patterns within

Snowflake:

schemas, role-based access control, masking, lineage, and metadata to support analytics and compliance.

•  Partner with product, ML/AI, BI, and engineering teams to translate business requirements into robust production-ready solutions.
•  Build monitoring, observability, and cost controls for compute, storage, and API usage related to document analytics and LLM integration.
•  Produce technical documentation, runbooks, and clear explanations of model/LLM behavior and limitations to non-technical stakeholders