Senior Snowflake/Data Consultant

Insight Global; Woonsocket (RI); On-site; USD 140,000 - 190,000; Full time

Job summary

Insight Global seeks a Senior Snowflake/Data consultant to support a large health insurance client. You will design unified data pipelines in Snowflake, enable document analytics, and implement NLQ interfaces with LLM integrations.

Collaboration with product and engineering teams is essential to deliver production-ready analytics solutions. The role emphasizes near-real-time and batch workloads, governance patterns, and cost controls.

Qualifications

• Experience designing data pipelines and Snowflake architectures.
• Strong programming skills in Python, Java, and C++.
• Hands-on data visualization experience with Tableau or Power BI.
• Knowledge of data governance, masking, and lineage patterns.

Responsibilities

• Design and implement unified data pipelines in Snowflake for structured, semi-structured, and document data.
• Build document analytics workflows including ingestion, text extraction, embeddings, and retrieval.
• Implement NLQ interfaces translating prompts into analytic queries and retrieval flows.
• Integrate Snowflake with LLMs for summarization, QA, and code-generation using External Functions/Snowpark.
• Develop RAG architectures leveraging Snowflake embeddings and vector indexes.
• Author Snowpark/Python/SQL transformations, streams, tasks, and orchestration for near-real-time workloads.
• Apply data modeling and governance patterns to support analytics and compliance.
• Collaborate with product, ML/AI, BI, and engineering teams to translate requirements into production-ready solutions.
• Establish monitoring, observability, and cost controls for compute, storage, and API usage.
• Produce technical docs, runbooks, and explain model/LLM behavior for non-technical stakeholders.

Skills

Statistical Analysis

Python

Java

C++

Data Visualization

Tools

Snowflake

Tableau

Power BI

SQL

NoSQL

Job description

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.

Skills and Requirements

• Statistical Analysis: Proficiency in statistical methods and software, such as Python, to analyze data.
• Data Visualization: Ability to create compelling visualizations using tools like Tableau, Power BI, and other cloud technologies.
• Database Management: Knowledge of SQL and NoSQL databases for efficient data storage and retrieval.
• 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