Data Analyst, Revenue Operations

NMI

6d•$65,000 - $85,000•Remote

About The Position

NMI is a leading provider of payment gateway solutions, specializing in card-present solutions and payment processing. Our innovative technologies empower businesses to securely accept payments and optimize transaction processes. With a focus on reliability, security, and innovation, we continuously push the boundaries of what's possible in the payments industry. 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.

Requirements

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

Nice To Haves

Familiarity with BigQuery ML a significant plus

Responsibilities

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
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