Principal Analyst, GTM Analytics

About Us

Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions.

As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites.

About the Role

Fivetran is building data pipelines to power the modern data stack for thousands of companies.

We’re looking for a  Principal Analyst to join our GTM Analytics team, where we turn data into the insights that shape decisions across Sales, Strategy, RevOps, Marketing, Deal Desk, and more. In this role, you'll be a force multiplier for the senior manager and a technical anchor for the broader team, taking on the most complex and time-sensitive questions across the business. When a request genuinely calls for a dashboard, you'll shape the requirements and propose the logic for our central data team to build.

In this role, you'll handle the team's most ambiguous and time-sensitive requests — often scoping a question live, in a meeting with senior stakeholders, and turning it into a usable answer quickly. You'll build models that blend statistical rigor and financial fluency (forecasting, pipeline coverage, quota simulation), review and unblock work from other team members, and represent the team's analytical judgment in rooms the senior manager isn't always in.

This is a full-time position based out of our Costa Rica office.

Technologies You’ll Use

SQL, dbt, Looker, Omni, Sigma, Excel and/or Google Sheets (financial modeling), Hex or similar notebook tools (exploratory analysis), Python (statistical libraries), Salesforce, Claude (or similar AI assistants)

What You’ll Do

Translate ambiguous, often verbal requests from senior stakeholders into a scoped analytical plan in real time

Build and maintain complex models that combine statistical and financial methods (e.g., pipeline coverage, quota simulation, forecast accuracy)

Deliver fast, directionally-correct analysis under time pressure, then refine to full rigor when the deliverable warrants it

Represent the team's analytical judgment in meetings with VP+ stakeholders without requiring the manager's involvement

Reframe stakeholder questions when the request as asked doesn't match the underlying business problem

Review and unblock analytical work from Level 2 and Level 3 team members

Triage incoming requests and help route them appropriately across the team

Own end-to-end delivery of strategic, cross-functional analyses (e.g., account matching strategy, end-of-quarter deal pattern analysis)

Apply statistical methods (e.g., regression, confidence intervals, cohort analysis) to strengthen the rigor of insights

Collaborate with Finance's own analysts when a request touches revenue or forecasting logic, to make sure GTM models stay consistent with how Finance defines and tracks those numbers

Skills We’re Looking For

Advanced, self-serve proficiency in SQL, dbt, and BI tools (Looker, Omni, Sigma) — able to independently get, analyze, and visualize data with minimal support

Strong understanding of SaaS sales motions (opportunity stages, pipeline progression, SFDC structure) and working knowledge of financial/forecasting concepts (ARR, quota attainment, pipeline coverage, bookings) — enough to collaborate confidently with Finance's own analysts, not to replace them

Statistical knowledge (e.g., regression analysis, distributions, confidence intervals) applied to business problems

Analytical mindset with the judgment to reframe a stakeholder's question when it doesn't match the underlying business problem

Ability to quickly scope and prioritize ambiguous requests under time pressure, often live in meetings, and strong judgment on when to move fast vs. when to prioritize rigor

Experience reviewing or mentoring others' analytical work

Comfortable operating with significant autonomy in front of senior or executive stakeholders

Bonus Skills​

Experience owning forecasting or planning methodology, not just reporting on it

Prior experience in FP&A or a quantitative finance role

Experience building simulation models

Some informal people leadership or team lead experience

Advanced Python (pandas, numpy, statsmodels)

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