Analytics Lead

About the role

Our Data & Analytics Platform team has migrated from Redshift to Snowflake, enabled 100+ users, and centralized all business data in under three months. We're a lean team with a clear remit: ensure a single source of truth for all business data. With Snowflake now adopted across the company, we're hiring an Analytics Lead to selectively expand this mandate to AI-first analytics and our highest-leverage data and analytics problems . This is a senior individual contributor role. You'll operate across three modes: pioneer (stand up net new analytics capabilities), special forces (identify and own the toughest, most critical-path data problems), and strategist (build a taxonomy, domain ontology, semantic layer, and other foundations that compound). No direct reports. Just real ownership, autonomy, and impact. About 30% of this role is stakeholder-facing. The teams you'll partner with often run on Airtable or spreadsheets today. You'll meet them where they are, know when to go deep versus ship a stopgap, and build things they'll actually rely on. If the boundary between technical rigor and pragmatic delivery is where you do your best work, this role is built for you. Our Data & Analytics Platform team has migrated from Redshift to Snowflake, enabled 100+ users, and centralized all business data in under three months. We're a lean team with a clear remit: ensure a single source of truth for all business data. With Snowflake now adopted across the company, we're hiring an Analytics Lead to selectively expand this mandate to AI-first analytics and our highest-leverage data and analytics problems . This is a senior individual contributor role. You'll operate across three modes: pioneer (stand up net new analytics capabilities), special forces (identify and own the toughest, most critical-path data problems), and strategist (build a taxonomy, domain ontology, semantic layer, and other foundations that compound). No direct reports. Just real ownership, autonomy, and impact. About 30% of this role is stakeholder-

Responsibilities

• Own and build out our AI-first analytics infrastructure end-to-end: semantic layer, LLM tooling, evals, and agents that analytically empower every team in the company.
• Maintain this AI-first analytics infrastructure so it doesn't decay as the business grows.
• Define and implement the taxonomy and domain ontology to match Expert Contributors to projects and tasks at scale. This is foundational to our marketplace business model.
• Architect a demand and supply model that gives leadership a shared, forward-looking view of where we're exposed and where to invest across domains, geographies, and acquisition channels.
• Identify the next highest-leverage opportunities where the Data Team can address a business-limiting constraint and help prioritize them.
• Be a trusted thought partner on data architecture, taxonomy, and analytics approach for operators, engineers, and executives across Snorkel.

Requirements

• 5+ years in data roles spanning analytics engineering, analytics, and data science, with comfort owning and moving between these types of work over the course of a project.
• SQL fluency, strong Python skills, familiarity with the modern data stack (e.g. Fivetran, dbt), and hands-on Snowflake or comparable cloud warehouse experience.
• High-autonomy IC track record: you don't need a team to get high-impact work done.
• Hands-on experience with modern AI tooling: LLMs, semantic layers, eval frameworks, and the infrastructure work required to put these into production.
• Experience identifying high-leverage opportunities in startups without a fully defined analytics agenda and comfort in going from 0-to-1 in high-growth environments.
• Genuine enjoyment of stakeholder partnership: you value co-defining problems and sharing findings with business and tech leads, rather than seeing it as a distraction.
• Bonus points for: Streamlit and/or Snowflake Cortex experience, familiarity with AI/data labeling, DaaS, or marketplace business models, experience building semantic layers or BI infrastructure, and A/B testing in marketplace or workforce platform contexts

Benefits

Additional Information

About Snorkel At Snorkel, we believe meaningful AI doesn't start with the model, it starts with the data. We're on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world's largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!

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