Marketing & GTM Data Analyst

As our first Marketing & GTM Data Analyst, you'll build the reporting and analytics function rather than inherit a finished one, and own the answer to what's working and where to invest next. You'll partner with the Director of Marketing Operations on the weekly GTM report leadership reads, and with our Decision Intelligence and Data Engineering teams on AI analytics agents and the GTM data foundation. Your work will power Marketing, Product, SDR, AE, Partnerships, and RevOps.

Responsibilities

Automate recurring GTM analytics with Decision Intelligence, designing and improving AI agents for weekly reporting, campaign and sales play readouts, scoring-model checks, and anomaly alerts; Own Marketing and GTM KPI definitions, calculation logic, and the weekly report leadership reads; Measure marketing campaigns and SDR/AE sales plays from first touch through closed-won using pre/post and cohort analysis; Create reusable campaign and sales play reporting templates with consistent definitions, time windows, and attribution rules; Own Dreamdata and evolve attribution practices, reconcile them with Salesforce and HubSpot, and turn attribution into budget recommendations; Evaluate and improve MQL, PQL, and account intent scoring models, with automated monitoring of precision, coverage, and conversion lift; Define and report partner and business development performance, including partner-sourced and influenced pipeline, co-marketing results, and performance by tier; Define GTM source-of-truth datasets with Data Engineering and Decision Intelligence, write the semantic context AI analytics agents rely on, and drive data quality fixes upstream

Requirements

Turns vague or complex requests into clear, answerable questions before touching data, and pushes back constructively when the question is wrong; Understands the B2B funnel (MQL, SAL, SQL, Closed Won) and how marketing, product-led, partner, SDR, and AE motions interact; Writes strong SQL directly in a warehouse and across Salesforce objects (Leads, Contacts, Campaigns, Campaign Members, Opportunities, custom objects); Reconciles messy data across systems, holds a high bar for what counts as right, and fixes problems at the source; Has owned or improved a multi-touch attribution setup and reconciled it with CRM data; Evaluates or tunes lead, PQL, or account scoring models and measures whether they improve conversion; Operates AI-native: builds AI agents or agentic workflows for analytics (e.g., Claude Code, MCP servers, n8n), automates recurring analysis, and writes the evaluation cases and context agents need; Builds dashboards and recurring reports in a BI tool that people rely on and act on, with a narrative sized for leadership; Owns KPI definitions so the same number means the same thing everywhere; Expected to actively use and experiment with advanced AI tools

Nice to have

Typically ~3–5 years in marketing analytics, GTM or revenue analytics, or a similar analytical role at a B2B SaaS company, or equivalent demonstrated experience; Hands-on with Dreamdata, HockeyStack, Bizible, or a similar attribution tool, plus HubSpot and Salesforce reporting; Python, and experience with dbt, semantic layers, or metric stores; Worked with intent data or partner attribution; Experience at a usage-based, developer-focused, or product-led business