Senior Snowflake​/Data Consultant

Senior Snowflake/Data Consultant

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

Required

Skills & Experience:

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 No

SQL 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.