Data Analyst, Revenue Operations

The Data Analyst, Revenue Operations is responsible for turning data from multiple source systems into the reporting, models, and visualizations that power revenue, sales, and operations decision-making. Reporting into the Revenue Operations organization, this role combines hands-on SQL and data modeling with predictive segmentation, opportunity analysis, and dashboard development — and serves as a trusted reporting partner to teams across the business.

You will work primarily within Revenue Operations while collaborating cross-functionally with Sales, Business and Technical Operations, Sales Enablement, Support, and Finance to get things done.

About NMI

NMI, a global leader in payment technologies, allows software and sales professionals to deliver payment innovations to their clients without having to build payment expertise in house. NMI enables our partners with choice, and challenges the one-size-fits-all approach to payments. You've probably used NMI in the last 24 hours without even realizing it. We're the platform that powers success for innovative tech created by SMBs, entrepreneurs and fintech startups.

We're creative problem solvers who help visionaries smash through boundaries and think beyond what's possible so they can think about what's next. But we're not just built for the tech savvy. We democratize the latest payments technology so that everyone can realize the benefits of easy payments across the full spectrum of commerce. Our mission is to use our expertise to enable more payments, in more ways and more places.

We provide ISOs, Fintech Innovators and Technologists the freedom to focus on what they do best, liberating them from restricted payment solutions and giving them access to the latest payment technology now and in the future.

How We Work - Our Core Values

Be a Good Person, It's Simple.

We treat everyone fairly and with respect. We lead with kindness, humility and integrity. We take the time to understand each other and our customers. And we serve with care, because customers are never a transaction, and always our focus

Align, Trust & Go.

We debate openly,  listen carefully and challenge thoughtfully. Once we decide, we move forward together - holding ourselves accountable to our commitments, and focusing on what matters most to our customers. That alignment creates momentum.

Raise the Bar.

Good enough isn't enough. We stay curious, measure everything, stay honest about progress and keep pushing ourselves to think creatively. We drive change, again and again. And leave things better than we found them. When we raise the bar, our customers feel it too.

The Ideal Candidate

You bring strong analytical thinking, intellectual curiosity, and a commitment to accuracy. You enjoy connecting information across disparate systems, identifying meaningful patterns, and delivering insights that influence business decisions. The opportunity to build and own these capabilities during your first year is something you find energizing:

• Build and maintain the core revenue and customer-lifecycle reporting that gives sales and revenue leadership clear visibility into performance, trends, and health of the business
• Develop and operationalize segmentation and predictive models in BigQuery ML that shape go-to-market targeting and account prioritization
• Lead the migration of dashboards from legacy datasets and BI tools into Tableau, with documented data lineage and custom measures
• Establish data quality and reconciliation practices that resolve entities across source systems and distinguish net-new from existing customers
• Partner with teams across the organization to translate ambiguous, evolving requests into concrete reporting deliverables

Key Responsibilities

• Deliver ad-hoc and recurring analyses supporting Sales, Business and Technical Operations (Salesforce Admins), Revenue, Sales Enablement, Support, and other internal teams, with minimal supervision
• Produce core revenue and customer-lifecycle reporting — including month-to-date, quarter-to-date, and trailing-twelve-month metrics — with validation logic that reconciles outputs against source-of-truth figures
• Author complex SQL in BigQuery using multi-CTE pipelines, window functions, user-defined functions, and array aggregation, and build reusable views for data aggregation and downstream consumption
• Build and refine segmentation and clustering models in BigQuery ML, including feature engineering, look-alike discovery, and cluster profiling, and operationalize model output into actionable deliverables for go-to-market teams
• Size addressable-market and ideal-customer opportunities by identifying accounts whose profile fits specific products, and quantify whitespace and upsell potential to support Sales Enablement and account prioritization
• Perform entity resolution across multiple source systems using fuzzy matching, normalization, and confidence scoring, reconciling records across platforms
• Develop and maintain Tableau dashboards for key business metrics, and lead migration from legacy datasets and BI tools with documented data lineage, custom measures, and visual mappings
• Maintain current knowledge of data sources and ongoing data warehouse developments, adapting models and reporting as schemas and requirements change
• Translate ambiguous and evolving requests from a wide range of stakeholders into concrete reporting specifications
• Contribute to a culture of data discipline, continuous improvement, and analytical excellence across the Revenue Operations organization
• Skills & Experience
• 2–5 years of experience in data analysis, revenue operations analytics, business intelligence, or a similar analytical role
• Strong SQL proficiency, with hands-on experience in BigQuery; familiarity with BigQuery ML a significant plus
• Demonstrated experience building and maintaining dashboards in Tableau or comparable data visualization tools
• Experience with data modeling and designing reusable views for aggregation and consumption
• Familiarity with entity resolution and data quality techniques, including fuzzy matching and cross-platform reconciliation
• Strong analytical skills with the ability to surface trends, identify gaps, and translate data into clear recommendations
• Experience working with CRM data (Salesforce preferred) and revenue/go-to-market datasets
• The ability to move fluidly between structured recurring reporting and ambiguous ad-hoc requests without losing rigor on either
• Strong written and verbal communication skills with the ability to partner effectively across technical and non-technical stakeholders

Salary range, depending on experience: $65,000 — $85,000 USD