Senior Product Manager, Data Products

Description

When the world's largest organizations bet on Mural, Govern & Trust is the team that earns that trust at scale. We build the experiences that help enterprises roll out Mural with confidence, keep it secure, and see the impact it has on how their people work. Data sits at the center of it all. Admins are Mural's most demanding data consumers: they need to prove ROI to their leadership, guide adoption across thousands of people, and account for every action. If data products can meet their bar, they'll work for everyone.

Mural has a modern data platform, strong data engineering and analytics teams, and a wealth of data on how teams collaborate. The next step is treating that data as a product in its own right, with a dedicated owner for what it means and how it's used.

YOUR MISSION

As a Senior Product Manager you'll define the metrics that describe how Mural creates value, and make them the shared foundation for everything built on top. The same definitions will power internal product decisions, the Insights experience Admins use in the product, and the reporting API and MCP server that customers and AI agents query.

This role starts upstream. You'll work from raw product events to decide what each metric should measure, how it's calculated, and what the data needs to look like for customers and internal teams to rely on it. Then you'll turn those metrics into experiences that help organizations understand and grow their use of Mural.

Responsibilities

• The evolution of data products. Shape how Mural's data products move from reporting on what happened to guiding what happens next. Work across the Govern & Trust portfolio to define how insights become part of how organizations run Mural.
• The metric layer. Define Mural's shared, cross-product metrics, like activity, collaboration, and adoption. Set the standards that let product teams define and publish their own metrics consistently. Data Engineering builds and runs the layer; you shape what goes in it and how it evolves.
• Internal product analytics. Be a thought partner to domain PMs as they set their north-star metrics, and make product data easy for them to explore on their own. Work with Business Analytics to keep product-facing and business-facing reporting working together.
• Customer-facing data products. Own the strategy and roadmap for Insights: in-product reporting and dashboards, exports and APIs, audit logs, and the methodology behind every number customers see.
• AI and agent access. Package and launch Mural's customer-facing reporting MCP server: which data it exposes, which plans get it, and what guardrails apply. Define how natural-language and agent-driven analysis extends Insights.
• Instrumentation. R&D teams own emitting events. Your job is to raise the bar on what they emit. Set per-product requirements for granularity and retention, which differ for audit logs, activity data, and product analytics. Partner with Data Engineering on event standards so metrics start from good data.
• WHAT YOU'LL BRING
• 5+ years of product management experience, including shipping at least one analytics or reporting product used by paying business customers. You defined the metrics behind it, not just the UI.
• A track record of making messy or conflicting data trustworthy: reconciling competing definitions, writing metric specs engineers could build from, and getting instrumentation changed upstream.
• Experience building both platform products, where your customers are internal teams or developers, and end-user-facing data products like analytics, reporting, or insights. You understand how the two have to work together.
• Working knowledge of modern data stacks: event pipelines, warehouses and lakehouses, dbt-style modeling, and semantic layers. You can write SQL and pull data yourself.
• The ability to get agreement on definitions across teams you don't manage, including PMs, data engineering, analytics, finance, and go-to-market.
• Experience with enterprise admin or governance products (IAM, security, compliance, audit)
• Hands-on experience with semantic layer tools (dbt Semantic Layer, Cube, LookML)
• Experience designing APIs, MCP servers, or connectors for analytics