NMI is powering the next generation of embedded payments with its modular payment acceptance platform and industry-leading gateway. Processing over $502 billion annually, we enable SaaS platforms, ISOs, PayFacs and banks to transform payments into a strategic advantage, driving growth, loyalty and new revenue streams.

Our modular, white-label platform puts partners in control, whether embedding payments into software or delivering payment services at scale. From no-code to full control API integrations, and from underwriting to compliance and risk monitoring, NMI handles the complexity so partners can focus on what matters most: their customers.

More than 6,000 technology partners trust NMI to deliver seamless, scalable payment experiences across online, in-app, in-store, mobile and unattended environments. However you are building the future of commerce, build it with NMI.

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.

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

Independent work ethic and comfort operating in a fast-paced environment where priorities and reporting requirements can shift