Senior Product Manager, Data
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Job Description
Senior Product Manager leading an enterprise context layer for AI agents, customer products, and finance automations. Driving data governance, stakeholder alignment, adoption, and AI product delivery.
Responsibilities:
- Lead discovery with business and technical stakeholders through working sessions, surface current data usage, and turn findings into prioritized use cases and requirements
- Own definitions and ownership by identifying inconsistent metrics and business terms and driving agreed, documented definitions with accountable owners
- Lead adoption across the business and secure leadership sponsorship and alignment
- Run a hypothesis-driven process by validating client assumptions through sessions or experiments and documenting clear verdicts and rationale
- Shape increments with the Solution Architect by defining scope, acceptance criteria and vertical-slice order based on value and risk
- Challenge technical decisions from a business perspective and push back on unsuitable data models, definitions or trade-offs
- Maintain cadence with the Project Manager by tracking decisions, open questions, risks and stakeholder commitments
- Transfer ownership through processes, documentation and an ownership model that keeps the layer accurate after engagement
Requirements:
- 5+ years in product management, with experience on data products (analytics, data platforms, metrics or semantic layers, internal data tools or similar)
- Experience aligning stakeholders across business areas on shared definitions, priorities and ways of working
- A structured, evidence-based approach to discovery and prioritization
- Comfortable making decisions with incomplete information and managing senior stakeholders
- A record of getting products adopted, not just delivered
- Experience in defining, designing and delivering AI or LLM-based products
- Fluent written and spoken English
- Enough technical depth to challenge data architects and engineers on technical definitions, modeling choices and trade-offs, and to understand their answers (strong plus)
- Familiarity with modern data stacks, for example Databricks, Snowflake, dbt, data catalogs or governance tooling (strong plus)
Benefits:
- Monthly USD Service Fee
- 20 business days of paid Agreed Time Off—Annual + 6 Local Holidays
- Caregiver Time Off
- A dynamic remote work culture. You can work from anywhere!
- An entrepreneurial environment.
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