Manager, Business Intelligence & Revenue Analytics
Listed on 2026-10-01
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IT/Tech
Data Analyst, Business Intelligence, Business Systems & Technology Analysis, Data Science Manager
Manager, Business Intelligence & Revenue Analytics
Salary range: $120K - $170K
Location:
San Francisco, CA
Visa Sponsorship Details:
Not open to any visas (e.g. US citizen, Green Card holders)
Hybrid work policy:
In-person 3 days per week in SF
About this role
The Manager, Business Intelligence & Revenue Analytics sits at the intersection of data, commercial insight, and people leadership. The Manager works closely with the Director to shape and execute the strategic direction of the BI and analytics function and is accountable for translating that direction into a prioritised analytics roadmap, high-quality execution, team performance, and professional development.
The role is responsible for helping define how data is leveraged to drive decisions across Product, Sales, Marketing, Revenue Operations, and Executive Leadership. In partnership with business stakeholders, the Manager develops reporting frameworks, analyses performance trends, identifies opportunities and risks, and ensures analytics investments support informed business decisions and measurable outcomes. The role also supports the development of customer-facing insights and product performance metrics that enhance transparency, customer experience, and product decision-making.
This is a hands-on leadership role. The Manager is expected to balance people leadership with direct analytical contribution, personally owning key initiatives and complex analytical work while coaching and developing a high-performing team. The role works closely with the Data Engineering function to ensure business requirements are accurately reflected in data models, transformation logic, and reporting outputs while helping define analytics requirements, priorities, and success measures.
The ideal candidate possesses strong SQL and reporting capabilities, a solid understanding of relational database concepts and data best practices, and the ability to communicate complex findings effectively to both technical and non-technical audiences.
Responsibilities
Revenue & Sales Analytics
- Partner with sales leadership to deliver reporting, forecasting, performance insights, and data-driven recommendations that support pipeline health, customer growth, product adoption, and revenue generation.
- Identify patterns in pipeline, churn, product adoption, and customer behaviour that translate into actionable sales recommendations and growth opportunities.
- Surface underserved segments, at-risk accounts, and areas of pipeline risk through ongoing data analysis.
- Present findings to sales teams and leadership in a clear, compelling format that drives informed decision-making.
Marketing Analytics
- Support marketing through campaign performance analysis, attribution, audience segmentation, and actionable insights that inform strategy and investment decisions.
- Track and report on marketing KPIs, helping the team understand what is working, what is not, and where to focus.
- Collaborate with marketing stakeholders to define success metrics and build reporting that reflects them.
KPI Reporting & Management Dashboards
- Develop and maintain KPI reporting frameworks, dashboards, and executive reporting that provide leadership with consistent, reliable visibility into business performance across sales, marketing, and operations.
- Ensure management reporting is consistent, timely, and tells the right story – not just accurate, but useful.
- Proactively flag performance trends, anomalies, and risks in a format that supports decision-making at the leadership level.
Data Collaboration & Systems
- Partner closely with the Data Engineering function to define analytics requirements, establish priorities, and ensure business needs are accurately reflected in data models, transformation logic, data pipelines, and reporting outputs.
- Maintain a strong understanding of database and table structure best practices sufficient to collaborate effectively with data engineering resources and contribute to data design discussions.
- Develop and maintain reporting logic, datasets, and reusable analytical assets that support reporting and business decision-making.
- Define, document, and maintain core business logic, including revenue metrics, customer segmentation, and product usage definitions, to ensure consistency across reporting and analytics.
- Establish and enforce data standards and governance practices that improve data quality, consistency, accuracy, and trust across reporting systems and analytics assets.
- Develop validation and reconciliation processes to…
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