Revenue Operations Analyst II

Responsibilities

• Own Dashboards & Reporting: Serve as the single point of accountability for GTM analytics delivery. Design, build, and optimize complex data models, calculated fields, and cross-source joins across our BI platforms to ensure scalable reporting.
• Deliver Executive-Ready Insights: Support Board meetings and operating reviews by distilling complex data into clear, strategic narratives. Deliver ad-hoc analysis for campaign performance, product launches, and segment deep-dives.
• Partner with GTM Leadership: Translate business questions from Sales, Marketing, and RevOps partners into precise reporting requirements. Track the full revenue funnel (MQL/SQL conversions, velocity, and win rates) and support the recurring forecast cadence with accurate pipeline reporting.
• Enforce Data Governance & QA: Build automated validation checks, reconciliation protocols, and regression testing to ensure data accuracy. Maintain comprehensive documentation, including data dictionaries, calculation logic, and source-to-dashboard lineage.
• Collaborate Upstream: Partner with Revenue Systems and Data Engineering to define data architecture requirements and advocate for upstream data quality within Salesforce and marketing automation tools.
• Drive AI & Innovation: Champion the adoption of AI-powered analytics tools (such as AI-assisted data exploration, predictive analytics, and natural language querying) to automate repetitive tasks and surface hidden data patterns.

Requirements

• Experience: 4-7 years in analytics, business intelligence, or data visualization within a B2B SaaS or high-growth environment.
• GTM Fluency: Deep understanding of Sales and Marketing KPIs, including pipeline coverage, win rates, deal velocity, CAC, LTV, and full funnel mechanics.
• Technical Skills: Advanced proficiency in at least one major BI platform (Power BI, Tableau, or Looker) building production-grade dashboards from scratch, alongside strong SQL skills for complex queries and data modeling.
• CRM Architecture: Deep understanding of Salesforce data architecture and experience building analytics on top of CRM data.
• Data Discipline: A strong QA mindset with experience building validation frameworks, paired with meticulous documentation habits (data dictionaries and calculation logic are a non-negotiable part of your process).
• Execution & Communication: Ability to thrive in a fast-paced environment, manage competing priorities, and translate complex technical concepts into clear insights for non-technical stakeholders.
• Marketing Integration: Experience integrating data from marketing automation platforms (e.g., Marketo, HubSpot, Pardot) into unified reporting views.
• Advanced Tools: Advanced Excel/Google Sheets proficiency for ad-hoc modeling.
• AI Curiosity: Active engagement with or exposure to AI analytics tools, AI copilots, or automated insight engines.
• Education: Bachelor's degree in Analytics, Data Science, Information Systems, Business, or a related field; advanced degrees or BI certifications are a plus.
• About AvidXchange
• A go-getter with an entrepreneurial mindset - that means you are not afraid of taking risks, winning big or facing the unknown.
• Someone who understands that business is people centric. Connecting with others as hum

Benefits

Additional Information

Job Overview The Revenue Operations Analyst II is the analytics engine behind AvidXchange's go-to-market (GTM) organization. In this role, you will own the design, development, and maintenance of Sales and Marketing dashboards and reporting, translating complex data into compelling visual narratives that help leaders make faster, better decisions. You already speak the language of Sales and Marketing KPIs fluently, bring a strong QA discipline and meticulous documentation habits, and know that trust in data is the foundation everything else is built on. You will partner closely with RevOps Partners, Sales, Marketing, and executive leadership to stay ahead of evolving business needs, while actively exploring how AI is transforming analytics to push the boundaries of what our data can tell us.

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