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Kadence builds workplace coordination software for hybrid work, serving over 650 customer organizations globally. You will lead the Data, Insights & Integrations Pod as Senior Product Manager, owning the Kadence insights platform—an analytics product used by real estate, workplace, and finance leaders at global corporations to make decisions about space utilization, usage patterns, and costs.
Your core responsibilities include:
**Strategy & Leadership**: Own the vision, strategy, and roadmap for the insights platform and integrations. Lead a cross-functional pod of engineers, data specialists, and designers. Work directly with clients ranging from workplace teams to C-suite executives.
**Discovery & Problem-Solving**: Conduct discovery sessions, workshops, and reviews that move beyond surface requests to uncover underlying decisions and pain points. Transform insights into dashboards, reports, metrics, and data products that answer executive questions: Do we have the right amount of space? Is our hybrid policy working? Where can we save money?
**Data Governance & Accuracy**: Own the semantic layer behind insights—shared metric definitions and data models that ensure every number shown to CFOs and CRE leaders is correct, consistent, explainable, and trusted. Present insights and product direction to senior stakeholders with clear data storytelling.
**Scaling & Pattern Recognition**: Identify patterns across clients and convert one-off requests into scalable product capabilities. Prioritize and shape the integrations roadmap (HR, identity, access-control, sensor, and BI systems).
**AI & Emerging Tech**: Lead how AI changes how clients get answers—natural-language questions over workplace data, AI-generated insights, and access to Kadence data through tools like Copilot, ChatGPT, and Claude via MCP. Set guardrails to keep answers accurate, governed, and safe.
**Cross-functional Collaboration**: Work with commercial, customer success, and marketing on positioning, go-to-market, and renewals. Break complex problems into clear, shippable steps and measure outcomes.
**Requirements**:
- Several years of product management in B2B SaaS with a proven track record shipping data, analytics, or insights products that customers rely on
- Modern data fluency with strong SQL skills; ability to write your own queries to explore data, validate hypotheses, and check numbers independently
- Understanding of semantic layers, metric stores, and how LLMs answer questions over structured data (text-to-SQL, retrieval, agents, tool use)
- Experience presenting to and influencing C-suite or senior leadership audiences; ability to translate analysis into decisions
- Consultative, client-facing style with strong discovery skills (interviews, data analysis, validation)
- Product thinking that scales; ability to turn single-client requests into multi-client capabilities
- Clear understanding of AI risk in data products: confidently wrong numbers, inconsistent answers, data leakage, prompt injection, and explainability
- Clear communication with executives, clients, and engineers
- Comfort with ambiguity, bias to action, and empathy for users
- Familiarity with Jira, Notion, Figma, and product analytics platforms
**Nice to Have**:
- Experience in workplace technology, corporate real estate, facilities, or proptech
- Background in analytics consulting, management consulting, or as a data analyst
- Hands-on experience with semantic layers or modern data stack (dbt Semantic Layer, Cube, LookML, Snowflake, Databricks) or embedded analytics
- Experience with enterprise integrations (HRIS, identity providers like Entra ID/Okta, access control, IoT sensors)
- Experience shipping LLM or agent features to enterprise customers, including evaluation frameworks, MCP, and AI governance reviews
