The Role
Manage and improve AI-driven conversational analytics on Snowflake: train and evaluate AI/NQL models, maintain semantic models and business knowledge layers, validate data quality, build KPIs and dashboards, perform ad hoc analysis and Excel financial/forecasting models, collaborate with stakeholders and data engineering to onboard data and improve AI response accuracy.
Summary Generated by Built In
Position Summary
AI & Semantic Layer Management
Requirements
Support the development, optimization, and ongoing maintenance of the company’s AI-powered analytics platform built on Snowflake. This role combines business analytics, semantic modeling, AI knowledge management, and data modeling to ensure conversational AI tools deliver accurate, reliable, and actionable insights.
AI & Semantic Layer Management
- Train, evaluate, and continuously improve enterprise AI/NQL models.
- Maintain and optimize semantic models powering conversational analytics.
- Improve AI response accuracy through prompt refinement, metadata management, and business rule configuration.
- Build and maintain business definitions, data relationships, and knowledge layers used by AI agents.
- Test AI-generated responses for quality, consistency, and business accuracy.
- Monitor AI performance and identify opportunities to improve response quality and adoption.
- Assist in developing AI agents within the Snowflake ecosystem.
- Support expansion of the Snowflake data platform.
- Validate newly integrated datasets and ensure data quality.
- Assist with onboarding new enterprise systems into Snowflake.
- Document data lineage, business logic, and transformation rules.
- Collaborate with data engineering teams on validation and troubleshooting.
- Perform ad hoc analysis supporting Pricing, Revenue Operations, Finance, and Operations.
- Develop KPI reporting and executive dashboards.
- Build pricing, forecasting, and operational models.
- Present findings and recommendations.
- Develop advanced Excel models for financial and operational analysis.
- Build forecasting, pricing, and scenario planning models.
- Maintain standardized analytical templates.
- Automate repetitive reporting processes.
- Validate data accuracy across enterprise systems.
- Maintain data dictionaries and business glossaries.
- Identify data quality issues and coordinate resolution.
- Document business rules and calculation methodologies.
- Partner with business stakeholders to understand requirements.
- Work with Data Engineering, IT, Pricing, Revenue Operations, and Finance.
- Translate business questions into analytical solutions.
- Support user testing and rollout of new AI capabilities.
- SQL
- Advanced Microsoft Excel
- Conversational Analytics / NQL
- Semantic Modeling
- AI Prompt Engineering
- Data Modeling
- ETL concepts
- Python
- 3–6 years in business analytics, analytics engineering, BI, or AI operations.
- Experience supporting enterprise data platforms.
- Experience with semantic layers or business metadata.
- Experience improving AI-generated outputs preferred.
- ERP experience preferred.
- Snowflake experience strongly preferred.
- Analytical and detail-oriented.
- Strong problem-solving skills.
- Excellent communication.
- Self-motivated in a remote environment.
- Comfortable working across time zones.
- Snowflake
- Microsoft Great Plains (ERP)
- Motive
- Holman
- HubSpot
- Power BI
- Microsoft Excel
- Internal AI Agents and Conversational Analytics Platform
- Snowflake Cortex AI
- Snowflake Cortex Analyst
- Power BI
- Snowpark
- Semantic Layer Design
- AI Agent Development
- LLMs
- Prompt Engineering
- RAG
- Metadata Management
- Revenue Operations Analytics
- Pricing Analytics
- Fleet Management
- Data Service Operations Analytics
This position serves as the operational owner of the AI analytics ecosystem, ensuring AI models, semantic definitions, and business knowledge remain accurate as enterprise data grows. The role combines AI operations with traditional business analytics, creating a high-impact resource that scales the organization's AI capabilities.
Requirements
Key Competencies
Education
Education
- Bachelor’s degree in Business, Computer Science, IT, or related field preferred.
- Equivalent work experience in cloud sales/technology will be considered.
- Microsoft Azure Fundamentals (AZ-900) certification is required.
- Advanced Azure certifications such as AZ-104, AZ-305, or equivalent are preferred.
- 3–5+ years in cloud sales, IT sales, or Microsoft licensing, with proven quota attainment.
- Demonstrated success in building pipeline and closing Azure or equivalent cloud deals.
- Experience co-selling with Microsoft AEs and leveraging Microsoft funding programs.
- Solid understanding of cloud concepts: infrastructure, data, AI, app modernization, security.
- Familiarity with Microsoft licensing models (EA, CSP) and Azure incentive structures.
- Understanding of cloud economics and migration frameworks.
- Strong consultative sales approach with ability to uncover customer needs and map solutions.
- Excellent communication, presentation, and negotiation skills.
- Relationship management with technical and business stakeholders.
- Strategic thinking with ability to connect technical features to business outcomes.
- Problem-solving, objection handling, and multi-tasking.
- Ability to collaborate effectively across internal teams and with Microsoft field resources.
- Autonomous with a strong sense of urgency and execution focus.
- Occasional travel to customer sites, Microsoft events, or team meetings (Canada and U.S.).
- Bilingual (English/French) is an asset but not required.
Skills Required
- Microsoft Azure Fundamentals (AZ-900) certification
- 3-6 years in business analytics, analytics engineering, BI, or AI operations
- Experience supporting enterprise data platforms
- Experience with semantic layers or business metadata
- Advanced Microsoft Excel and financial/forecasting modeling
- Familiarity with Snowflake (strongly preferred)
- Conversational Analytics / NQL and semantic modeling experience
- AI prompt engineering and improving AI-generated outputs
- Python
- ETL concepts and data modeling
- Knowledge of Microsoft Azure infrastructure, licensing models (EA, CSP), and cloud economics
- Bachelor's degree in Business, Computer Science, IT, or equivalent experience
- Experience in cloud sales, IT sales, or Microsoft licensing with quota attainment
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Booth & Partners is a leading outsourcing and offshoring consulting firm that helps over 150 clients worldwide solve their talent and workspace challenges by specializing in building remote teams for startups and scaling businesses.
