[All remote jobs](https://jobicy.com/jobs.md)[![Mural logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2022/01/9b6f1383-221.jpeg)](https://jobicy.com/company/mural.md)[Mural](https://jobicy.com/company/mural.md) # Senior Product Manager, Data Products Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/mural.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUSD 177,160–221,450 / yrDepartment[Product & Operations](https://jobicy.com/categories/management.md)EmploymentFull TimeExperienceSeniorPublished27 Oct 2026Apply before26 Nov 2026Listing views70Application actions3Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. Mural is seeking a Senior Product Manager to own the strategy, definitions, and customer experience for enterprise data products. The role establishes a shared metric layer across product analytics, customer Insights dashboards, exports, APIs, audit logs, and an MCP server. This PM will partner closely with data engineering, analytics, finance, go-to-market teams, and domain product managers to make data trustworthy and actionable. Success requires strong product leadership alongside hands-on fluency in SQL, event instrumentation, semantic layers, and enterprise governance needs. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a senior, highly cross-functional product role involving ambiguous data definitions, technical platform decisions, and customer-facing enterprise products. The candidate must align many stakeholders while setting standards that affect multiple product teams and external customers. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$199,305US market range (per year)$175k–$235k0$258.50k AI insightThe employer discloses a credible annual base-pay range of $177,160–$221,450 USD, with a midpoint of $199,305. The estimated US market range for a senior product manager specializing in data products and analytics is $175,000–$235,000 annually. ## Core skills Skills and capabilities most closely associated with this opportunity. [Product strategy](https://jobicy.com/jobs?search_keywords=Product%20strategy.md)[Data product management](https://jobicy.com/jobs?search_keywords=Data%20product%20management.md)[Product analytics](https://jobicy.com/jobs?search_keywords=Product%20analytics.md)[Metric definition](https://jobicy.com/jobs?search_keywords=Metric%20definition.md)[SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[Event instrumentation](https://jobicy.com/jobs?search_keywords=Event%20instrumentation.md)[Semantic layers](https://jobicy.com/jobs?search_keywords=Semantic%20layers.md)[Data governance](https://jobicy.com/jobs?search_keywords=Data%20governance.md)[Analytics dashboards](https://jobicy.com/jobs?search_keywords=Analytics%20dashboards.md)[Reporting APIs](https://jobicy.com/jobs?search_keywords=Reporting%20APIs.md)[MCP servers](https://jobicy.com/jobs?search_keywords=MCP%20servers.md)[Roadmap management](https://jobicy.com/jobs?search_keywords=Roadmap%20management.md)[Stakeholder alignment](https://jobicy.com/jobs?search_keywords=Stakeholder%20alignment.md)[Enterprise SaaS](https://jobicy.com/jobs?search_keywords=Enterprise%20SaaS.md) Sample interview questionsHow would you create a shared definition for a metric such as product adoption when different teams use conflicting definitions?I would begin by mapping each current definition to its intended decision and audience, then identify common events, entities, time windows, and exclusions. I would facilitate a decision process with product, analytics, finance, and engineering stakeholders, document the approved definition in a versioned metric specification, and establish ownership and change-control rules. Finally, I would validate the metric against known customer and internal use cases before publishing it through the semantic layer. Describe how you would improve event instrumentation for a product analytics and audit-log use case. I would separate the requirements because product analytics optimizes for behavioral analysis while audit logs require traceability and retention. I would define required event names, actor and resource identifiers, timestamps, context fields, privacy classifications, retention rules, and data-quality checks. With engineering, I would prioritize instrumentation gaps based on customer value and decision impact, then monitor completeness and schema adherence after release. What factors would guide your roadmap for customer-facing reporting APIs and an MCP server? I would prioritize validated administrator workflows, customer demand, data quality, entitlement requirements, and security risks. The roadmap would define a stable core metric set, permissions and tenant isolation, rate limits, auditability, documentation, and clear plan packaging. For an MCP server, I would also establish guardrails for natural-language queries, response scope, sensitive-data handling, and reliable interpretation of metric definitions. How do you balance internal analytics needs with external customer reporting needs? I would build a shared governed metric foundation while recognizing that the interfaces and service expectations differ. Internal teams may need exploratory and rapidly evolving analysis, whereas customers need stable definitions, transparent methodology, permissions, and dependable APIs. A semantic layer and documented contracts help reuse logic while allowing separate delivery surfaces and release processes. Tell us how you would measure whether the Insights product is successful. I would use a balanced scorecard covering adoption, engagement, decision value, trust, and operational quality. Example measures include activated admin accounts, recurring dashboard and export usage, API adoption, time to answer administrative questions, data accuracy incidents, and customer feedback on ROI visibility. I would pair these indicators with qualitative research to confirm that usage is helping organizations take meaningful actions rather than merely viewing reports. Opportunity details ## About this role. ### ABOUT THE TEAM 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. ### WHAT YOU’LL DO * 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 ### Equal Opportunity We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. 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