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Revenue Analytics Manager

Job in Austin, Travis County, Texas, 73301, USA
Listing for: Fundraise Up, Inc.
Full Time position
Listed on 2026-11-05
Job specializations:
  • Marketing / Advertising / PR
    Digital Marketing, CRM Systems & Management
Salary/Wage Range or Industry Benchmark: 149000 - 162000 USD Yearly USD 149000.00 162000.00 YEAR
Job Description & How to Apply Below
About Fundraise Up

We’re Fundraise Up - a global fundraising platform built to make donating to nonprofits fast, seamless, and accessible to all. Every month, our technology powers tens of millions of dollars in donations across the globe. We focus on innovation that directly impacts results: faster load times, higher conversion rates, global payment support, and accessibility-first design.

Our platform is trusted by many of the world’s leading nonprofits, including UNICEF, the Alzheimer’s Association, and a wide range of global NGOs. With a 4.9/5 rating across top software review platforms, we’re recognized not just for our impact - but for the quality of the product we deliver.

About

The Role

Pipeline doesn't grow because a campaign launched. It grows because someone traced the data back to what actually worked and did more of it.

As Revenue Analytics Manager, you own the analytics layer connecting Marketing, Partnerships, and Sales. You build the dashboards, models, and lead-routing logic that turn campaign and partner activity into predictable revenue. You sit inside Revenue Operations and work daily with Marketing, Partnerships, Sales, and Finance to make sure every dollar spent on demand generation and every partner-sourced lead is tracked, attributed, and acted on.

This is an individual contributor role. The Manager title reflects ownership of revenue analytics processes, systems, and reporting, not management of direct reports.

Key Responsibilities
  • Build and maintain dashboards and reports tracking demand generation and partnership performance (MQLs, SQLs, pipeline, ROI)
  • Analyze campaign, channel, and partner performance data to shape Marketing and Partnerships strategy
  • Partner with Marketing to design and optimize multi-channel campaigns across paid, organic, email, and events that drive qualified pipeline
  • Partner with Partnerships to track and improve co-marketing, referral, and affiliate program performance
  • Build and maintain attribution models and lead scoring that connect marketing and partner activity to revenue outcomes
  • Work with Finance to build models and forecasts for marketing and partnership-sourced pipeline
  • Manage lead routing and handoff processes between Marketing, Partnerships, and Sales
  • Turn data findings into clear recommendations for stakeholders across departments
  • Design process improvements that scale demand generation and partner operations as the team grows

At Fundraise Up, AI is a default tool, not an experimental one. We expect every team member to actively use AI in their day-to-day work, identify where AI can change the shape of problems in their function, and grow their fluency as the tools evolve. For this role, that means using AI to accelerate analysis, surface patterns across campaign and partner data faster, and reduce manual reporting work.

Skills and Qualifications

Must-Haves

  • 3+ years of experience in Rev Ops focused on Demand Generation, Marketing Operations, or Partnerships/Channel Ops
  • Strong SQL skills
  • Fluency in Excel or Google Sheets
  • Experience with a data visualization tool such as Looker, Tableau or PowerBI
  • Hands-on experience with a marketing automation or CRM platform such as Hub Spot, Marketo, or Salesforce
Nice to Have
  • Startup or SaaS company experience
  • Familiarity with attribution or web analytics tools such as Google Analytics, Marketo Measure (Bizible), or Segment
  • Knowledge of partnership and affiliate management platforms such as Partner Stack, Impact, Crossbeam, or Reveal
  • Working knowledge of paid media platforms such as Google Ads, Linked In Campaign Manager, or Meta Ads Manager
You’ll Thrive Here If You…
  • Can turn a messy dataset into a clear recommendation without being asked twice
  • Take ownership of a metric and chase it down when the number looks…
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