Revenue Intelligence Analyst

Dialpad•Austin, TX

9h•Hybrid

About The Position

As a Revenue Intelligence Analyst, you will turn Dialpad’s revenue data into actionable insights, scalable reporting, AI-enabled automation, and decision support for the go-to-market organization. This role sits on the Planning and Governance team and blends data analysis, reporting, understanding of business systems, AI agent automation, and strong business partnership. You will build and maintain dashboards, define and enhance datasets in BigQuery, automate recurring reporting, identify opportunities to deploy AI agents and workflow automation, and translate business questions into clear reporting and analytical solutions. You will also serve as a key liaison between business stakeholders and data or systems teams, ensuring that reporting outputs and automation solutions align with business needs. Your work will help leaders understand pipeline performance, forecast trends, operational health, and broader business performance with greater clarity, speed, and confidence. This position reports to the Director, Revenue Ops Planning & Governance, and has the opportunity to be based in our Austin or Tempe offices.

Requirements

2+ years of experience in analytics, business intelligence, revenue operations, or business systems analysis.
Experience building AI agents using Claude, Glean, ChatGPT, Gemini for process standardization, simplification, and automation.
Experience building dashboards and reports in Tableau.
Working knowledge of Salesforce data and reporting concepts.
Experience supporting Sales, RevOps, or SaaS go-to-market teams.
Strong analytical thinking and comfort working with large datasets.
Experience gathering business requirements and translating them into reporting solutions.
Strong communication skills across technical and non-technical audiences.
Ability to simplify complex data into clear, executive-ready insights.
High attention to detail and strong ownership mindset.
Bias toward automation and scalable reporting solutions.

Nice To Haves

Bachelor’s degree in Business, Finance, Economics, Data Analytics, Information Systems, or a related field.
Experience in a multi-segment SaaS environment.
Exposure to pipeline and forecast analytics.
Experience supporting post-sales functions such as Customer Success, Professional Services, Solutions Engineering, and Customer Experience.
Experience supporting executive-level reporting and ad hoc business analysis.
Familiarity with SaaS revenue metrics such as pipeline coverage, conversion rates, forecast variance, GRR, and NRR.
Experience working with BigQuery or similar cloud data warehouses.
Proactive, structured problem solver.

Responsibilities

Own executive reporting across the revenue (pre and post-sales) organization.
Deliver high-quality monthly, quarterly, and ad hoc reporting for senior leadership.
Synthesize complex data into clear business narratives and recommendations.
Create holistic reporting views that connect performance across teams, segments, and motions.
Ensure leaders have timely, accurate, and decision-ready insights.
Act as a liaison between business stakeholders and data, systems, and business operations teams.
Gather business requirements and translate them into reporting, dashboard, and dataset needs.
Define new datasets and enhance existing datasets in BigQuery to support evolving business questions.
Partner with technical teams to improve data availability, usability, and reporting readiness.
Help ensure reporting solutions align with business processes and system design.
Design and build executive-ready dashboards in Tableau.
Standardize reporting frameworks across revenue segments.
Develop intuitive visualizations for pipeline, forecast, productivity, retention, and expansion.
Translate business questions into scalable dashboard solutions.
Create reusable Tableau data sources and reporting assets.
Analyze revenue performance trends and deliver actionable insights to business stakeholders.
Build automated reporting that reduces manual spreadsheet work and improves reporting speed and consistency.
Support ad hoc, cross-functional analysis across pipeline, bookings, forecast, productivity, and customer metrics.
Identify reporting gaps and recommend new metrics, views, or process improvements.
Partner on root-cause analysis to explain performance changes and business trends.
Design and deploy AI agents and workflow automations that streamline recurring reporting, data QA, and stakeholder request intake across RevOps workflows.
Evaluate high-impact opportunities to apply AI across reporting and analysis processes, partnering with systems and data teams to operationalize solutions and measure adoption, accuracy, and efficiency gains.
Analyze sales processes for inefficiencies and implement AI agents to standardize and automate workflows.