The opportunity
Our GTM org has a lot of questions. Most of the questions we care about can’t be answered by spinning up a cute dashboard.
What you'll do
An experienced analyst. You have roughly 8 years of hands-on, highly: technical analytics experience. Most importantly: you’re backed by the pattern recognition that comes with having seen all sorts of hairy problems. You’re at the point in your career where you can take an ambiguous business question, dive head-first into the data, turn your findings into a decision, and bring everyone else along with you.
A bridge between the technical and the business. You can build a model in: dbt, work directly in Snowflake, and translate it into something actionable. You’ll partner closely with our Lead Analytics Engineer but you need to be willing and able to dive in and self-serve.
Fluent in the quirks of GTM data. Attribution, channel definitions, UTMs,: bots and broken tracking are known quantities. You don’t need to have been a dedicated GTM Analyst, but you should certainly know your way around this part of the business.
Pushing the boundary of what AI means for analytics. AI is writing your: first-draft SQL, analysis, and reporting and you’ve shifted that energy to bringing analysis into the future: building the semantic layers, context, and guardrails that let the team self-serve trustworthy answers.
A trusted cross-functional leader. Teammates across functions and levels: listen to you. You immerse yourself in the context of their needs and bridge gaps in understanding.
Fiercely independent and accountable. You welcome a vague ask with aplomb.: You’ll scope the problem, find the dependencies, bring in the right people, and drive the work through the analysis, recommendation…all the way to a fix.
What they're looking for
- More concerned with impact than output. A polished dashboard is useful only: when it changes what we do. You prioritize the questions that can materially improve acquisition, conversion, retention, and revenue.
- Make our GTM data trustworthy. You’ll define metrics, model the funnel from: first touch through paid conversion, and reconcile discrepancies across Snowflake, Segment, Amplitude, GA4, and our ad platforms.
- Explain what we’re seeing. Why are trials up while paid conversion isn’t? Why: are Snowflake and Amplitude disagreeing? Which channel is driving volume but producing low-quality customers? You’ll dig into the data until we understand what changed and why.
- Help decide what to do next. Are we on track to hit our goals? What would: another investment in paid media produce? You’ll forecast, model the tradeoffs, and empower leadership to make the best possible decision.
