Director, Revenue Analytics & AI Innovation

10+ years of experience in data engineering, analytics engineering, or revenue/GTM analytics, including experience leading or building technical teams.

Deep hands-on expertise in data engineering and analytics engineering (e.g., SQL, dbt, modern data warehousing, ETL/ELT pipelines).

Proven experience designing and owning semantic and data models that serve multiple stakeholders, from analytics and BI to AI use cases.

Demonstrated experience leading AI adoption or AI-enabled transformation within a GTM or Revenue organization.

Strong, current knowledge of the AI vendor, tooling, and trends landscape, with the judgment to separate hype from real value.

Experience partnering closely with Revenue/GTM systems and strategy & operations functions.

Note

: We have even more benefits than listed

here

and below, your recruiter will provide more in-depth information as you continue in the interview process. Benefits are subject to individual plan requirements and eligibility criteria.

Health, Dental, Vision benefits start on your first day at Spring. You and your dependents also receive access to

One Medical

Architect and own the unified semantic and data layer that underpins Revenue Operations — the single source of truth connecting Sales, Marketing, Customer Success, and Finance data.

Define and drive the AI transformation strategy for Revenue Operations, identifying where AI and automation can meaningfully improve GTM efficiency, forecasting, and decision-making.

Build and lead a small, highly technical team of data/analytics engineers, operating as a true player-coach who still writes code and ships models personally.

Design and maintain core data models, pipelines, and analytics products that deliver actionable insight across the revenue organization — from individual contributors to executives.

Partner closely with the Systems and Strategy & Operations teams to ensure data architecture, tooling, and process are tightly aligned across RevOps.

Evaluate, pilot, and deploy AI tools and vendors, staying ahead of the fast-moving AI landscape and translating emerging capabilities into practical, high-value use cases.