Principal Analyst, GTM Analytics

Snowflake
US-CA-Menlo ParkPosted 25 March 2026

Job Description

Principal Analyst, GTM Analytics Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level. Snowflake is hiring a Principal Analyst, GTM Analytics within the Data Analytics and AI org (DAA). This role will serve as the dedicated analytics partner for the Services Delivery (SD) organization, owning the data strategy, reporting, and analytical frameworks that drive visibility into SD operations, project delivery, and use case outcomes. You will be responsible for ensuring our data infrastructure is accessible across multiple surfaces—from executive dashboards to autonomous AI agents—directly boosting the productivity of our Field and Delivery teams. This role requires in-person attendance in either our Menlo Park (CA), Dublin (CA), Bellevue (WA), or New York (NY) office at least 3 days per week. IN THIS ROLE YOU WILL: - Certify the Foundation: Own the development of "Gold Standard" analytical data models (via dbt) for Services Delivery. You will ensure every metric—from billable utilization to project margins—is accurate, governed, and ready for both executive reporting and AI consumption. - Translate Business Logic to AI Models: Act as the lead translator between Services leadership and technical systems. You will take complex business rules (e.g., revenue recognition patterns or resource leveling logic) and implement them into AI-friendly data models that power predictive tools. - Build for Multi-Surface Accessibility: Architect data infrastructure that isn't just for dashboards. You will ensure our Services data is structured to be accessible across multiple surfaces—whether it’s a Streamlit app, a Slack bot, or an autonomous AI agent. - Drive AI Self-Service & Productivity: Directly boost the productivity of our global delivery team by providing "Natural Language" data solutions. You will enable business users to query complex project data themselves using AI-driven interfaces, reducing the reliance on manual ad-hoc reporting. - Ensure Data Excellence: Manage the technical reconciliation between CRM/PSA systems (Salesforce) and internal data models to ensure 100% data integrity across all reporting surfaces. - Measure the Transformation: Develop and lead the measurement framework for our AI initiatives. You will conduct deep-dive analyses to prove how AI is changing our delivery speed, quality, and margins, providing the data-backed narrative for our services evolution. - Bridge the Gap: Partner closely with Analytics Engineering, Product, and the wider DAA team to ensure the "plumbing" of our data infrastructure supports the high-velocity needs of a global Services Delivery organization. OUR IDEAL CANDIDATE WILL HAVE: - Technical Mastery: 10+ years of experience in Analytics/BI within large-cap tech companies or high-growth SaaS environments; featuring expert-level SQL and hands-on dbt proficiency for production-grade data modeling. - AI & Infrastructure Literacy: Deep understanding of how to build "AI-ready" data structures—specifically for LLM consumption and agentic interfaces—using Python and data app frameworks like Streamlit. - Services Domain Expertise: Deep familiarity with Professional Services or Consulting operations and the CRM/PSA ecosystem (e.g., Salesforce). You have a firm grasp of the "Resource-to-Revenue" lifecycle and the technical data structures required to measure global delivery. - Strategic Leadership: The ability to navigate high-level strategy with executives while remaining "hands-on-keys" to build solutions and lead the technical roadmap. - Elite Communication: Proven ability to translate complex technical architectures and data deep-dives into clear, actionable narratives for non-technical stakeholders. Snowflake is growing fast, and we’re scaling our team to he ... (truncated, view full listing at source)
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