Vibe Coder : Datawarehouse

K12 Coalition is looking for a highly technical, AI-first Snowflake Data & AI Engineer to help build and own our next-generation enterprise data platform.

This person will be responsible for building and maintaining a centralized data lake/data platform in Snowflake, integrating data from systems across the organization, and developing a deep understanding of how that data connects across our businesses.

The role goes beyond simply moving data into Snowflake. We need someone who can understand the data inside and out—where it comes from, what it means, how entities relate across systems, how it should be modeled, and whether it can be trusted.

A major focus of this role will be building an LLM-powered reporting and analytics layer on top of Snowflake. Our goal is to enable business users to ask questions in natural language and receive accurate, explainable answers directly from our enterprise data rather than depending exclusively on traditional dashboards and manually created reports.

This is not a traditional data engineering role where success means pipelines are running. We want someone who can own the data foundation and help us rethink how employees interact with organizational data through AI.

Responsibilities

• Architect, build, and maintain our enterprise data lake/data platform using Snowflake
• Integrate data from multiple business systems, databases, APIs, SaaS platforms, and other data sources
• Build reliable ELT/ETL pipelines to ingest, transform, normalize, and maintain enterprise data
• Develop a deep understanding of the data across the organization, including its meaning, ownership, quality, lineage, and relationships
• Design scalable data models that accurately represent customers, users, products, transactions, organizations, activities, and other core business entities
• Identify and resolve inconsistencies, duplicates, missing data, conflicting definitions, and data-quality issues across source systems
• Establish relationships between data originating from different systems and business units
• Create and maintain clear data dictionaries, metadata, lineage, business definitions, and documentation
• Partner directly with business stakeholders to understand how they use data and translate business questions into reliable data models
• Build a semantic/business layer that allows AI systems to correctly understand organizational terminology, metrics, relationships, and business rules
• Design and implement LLM-powered reporting and analytics capabilities on top of Snowflake
• Enable natural-language questions such as What caused enrollment to decline last quarter or Which customers are most likely to renew based on historical behavior
• Develop AI agents and workflows capable of translating business questions into queries, retrieving the appropriate data, analyzing results, and presenting understandable answers
• Implement guardrails that reduce hallucinations and ensure AI-generated answers are grounded in trusted enterprise data
• Create methods for validating AI-generated queries, calculations, metrics, and responses
• Implement appropriate data governance, role-based access, security, and privacy controls
• Optimize Snowflake performance, storage, compute usage, and cost
• Use AI development tools such as ChatGPT, Claude, Cursor, Claude Code, and similar technologies to accelerate development and analysis
• Continuously evaluate emerging approaches for combining structured enterprise data, Snowflake, semantic models, AI agents, and LLMs

Required Qualifications

• 5+ years of experience in data engineering, data architecture, analytics engineering, or similar roles
• Strong hands-on experience with Snowflake
• Advanced SQL skills
• Strong experience with Python
• Experience designing enterprise data warehouses, data lakes, or lakehouse architectures
• Strong understanding of relational data modeling, dimensional modeling, normalization, and entity relationships
• Experience building and maintaining ETL/ELT pipelines
• Experience integrating data from APIs, relational databases, SaaS platforms, and other enterprise systems
• Ability to investigate unfamiliar datasets and quickly understand their structure, meaning, relationships, and business purpose
• Strong understanding of data quality, lineage, governance, and master-data concepts
• Experience working with large and complex datasets
• Experience working with LLMs and generative AI
• Understanding of techniques for grounding LLM responses in enterprise data
• Experience using AI-assisted development tools
• Strong problem-solving and analytical skills
• Ability to communicate technical data concepts to non-technical business stakeholders
• Self-motivated and able to independently own complex data problems
• Ability to communicate effectively in English with US-based stakeholders and team members
• Reliable high-speed internet connection and remote work environment suitable for virtual collaboration
• Available to collaborate during overlapping US business hours

Preferred Qualifications

• Experience with Snowflake Cortex, Cortex Analyst, Cortex Search, or Snowflake Intelligence
• Experience building natural-language-to-SQL or conversational analytics solutions
• Experience developing semantic models or semantic layers for enterprise analytics
• Experience with dbt or similar data transformation frameworks
• Experience with data cataloging, lineage, and observability tools
• Experience implementing Retrieval-Augmented Generation (RAG) architectures
• Experience developing AI agents that interact with structured enterprise data
• Experience with Azure or AWS
• Experience integrating platforms such as Salesforce, HubSpot, LMS platforms, financial systems, marketing systems, or other enterprise SaaS applications
• Understanding of data governance, security, RBAC, and privacy requirements
• Experience replacing or augmenting traditional BI/reporting workflows with AI-driven analytics
• Experience working remotely with US-based companies

What Success Looks Like

Within this role, success means we have a trusted enterprise data foundation where information from across K12 Coalition can be connected, understood, and queried consistently.

The successful contractor will:

• Build a scalable and reliable Snowflake data platform
• Understand our data and its relationships at a deep level rather than simply maintaining pipelines
• Establish trusted definitions for important business metrics and entities
• Improve data quality and visibility across systems
• Make it easy to determine where data originated and how it was transformed
• Create an AI-ready semantic layer that gives LLMs the context needed to correctly interpret our data
• Enable employees to ask business questions in natural language and receive accurate, data-backed answers
• Build validation and guardrails so AI-generated reporting can be trusted
• Reduce the amount of manual effort required to create reports and analyze business performance
• Continuously identify new ways that AI agents can analyze and interact with enterprise data

The ultimate goal is to move toward an environment where Snowflake serves as the trusted enterprise data foundation and LLMs become the primary interface through which employees explore, analyze, and understand that data.

Contract Details

• Independent contractor position (40 hours per week)
• Remote work from the Philippines
• Flexible working hours with overlap to US business hours as needed
• Long-term contract opportunity
• Compensation based on experience and skill level
• Contractor responsible for local taxes, equipment, and internet connectivity