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Rippling is a unified platform for HR, IT, and Finance that brings together workforce systems—payroll, expenses, benefits, computers, and third-party apps—into a single system. The company has raised $1.85B+ from top-tier investors and is headquartered in San Francisco.
Rippling recently launched Data Cloud, a new product that helps customers understand and act on data across their business by combining first-party, third-party, and customer-created data from HR, IT, finance, and external systems. This role is Product Lead for Analytics within Data Cloud.
You will own the vision, strategy, roadmap, and execution for Analytics within Rippling's Data Cloud. Your responsibilities include:
• Define and build new AI-centric experiences for how customers analyze data, extending beyond classic reports and dashboards
• Make sophisticated analysis intuitive for admins and business users while giving advanced users the depth and flexibility they need
• Build agentic experiences that help customers investigate questions, explain trends, and proactively discover meaningful events in their data
• Own customer-facing analytics experiences and shared capabilities that power analytics across Rippling
• Partner with your India-based engineering team and cross-functional stakeholders (engineering, design, AI, Data Catalog) across India and the USA to deliver trusted analytics
• Work directly with enterprise and mid-market customers to understand needs, drive adoption, and measure value
• Use AI extensively to accelerate discovery, prototyping, delivery, and product iteration
Your core engineering team is based in India, and you will work closely with teams across India and the USA.
REQUIREMENTS:
• 8+ years of product management experience with a track record of shipping complex B2B products
• Experience building analytics, BI, data platforms, or adjacent products; experience with shared platform capabilities is valuable
• Strong customer and UX judgment, with the ability to make sophisticated analysis intuitive without sacrificing power
• Technical fluency in data modeling, querying, metrics, and permissions, and the ability to work closely with engineering on product trade-offs
• AI fluency: understanding of how to build reliable AI and agentic experiences, evaluate their quality, and use AI effectively in your own work
• Strong systems thinking, clear communication, and the ability to drive execution across teams and geographies with high ownership
• Alignment with Rippling's leadership principles: pushing the limits of possible, challenging each other directly, and going and seeing
