Product Analytics Manager

Pinwheel•New York, NY

About The Position

Pinwheel is looking for an Analytics Manager who will serve as a strategic partner across Product, Engineering, Design (EPD), and Go-to-Market (GTM) teams. This role goes beyond dashboards—it’s about proactively driving insights, surfacing high-impact opportunities, and shaping product and business strategy. You’ll help Pinwheel understand not just what is happening in our products, but why, by combining quantitative and qualitative signals, and business context to guide decisions across the organization. You’ll play a critical role in influencing roadmap priorities, shaping customer best practices, and empowering our teams with clear, actionable insights.

Requirements

5+ years of experience in product analytics or a related data strategy role
Expert-level SQL skills and comfort with large, complex data sets
Deep experience with LookML
Strong understanding of data architecture, with the ability to ensure accuracy in metric definitions and event capture
Proven ability to partner cross-functionally—especially with Product, Engineering, and GTM teams—to influence strategic direction
Track record of proactive insights: not waiting for requests; finding patterns that drive impact
Excellent communicator, able to distill complexity into clear stories that drive action

Nice To Haves

experience with DBT and Fintech products

Responsibilities

Own analytics across Pinwheel’s product suite, focusing on conversion optimization and understanding customer and platform-level implementation patterns that drive success
Proactively identify trends, opportunities, and anomalies in product metrics—not just answering data questions; asking better ones
Develop metrics frameworks and KPI dashboards to monitor product performance, conversion funnels, and integration health across hundreds of partners
Partner with EPD and GTM teams to translate insights into action, informing product improvements and go-to-market narratives
Build a deep understanding of customer segments, product placement, and configuration performance to inform best practices for our partners and customers
Enable Sales and Marketing with case studies and metrics that highlight success factors across high-performing customers and integrations
Partner with Engineering and Data teams to ensure proper instrumentation, metric definitions, and data model design
Develop a system to ingest and synthesize qualitative feedback (e.g. Gong calls, Slack feedback, user surveys, and interviews) into unified insights about product opportunities