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The Principal Product Manager for Data Platform is a senior individual contributor role responsible for shaping the strategy, direction, and business impact of FYUL's shared data capabilities. This is a high-leverage position defined by organizational scope rather than team size—you will own strategy across Data Platform, Data Analytics, Business Intelligence, AI-enabled analytics, and the teams that produce and consume data across the company.
You will treat the Data Platform as a product serving analysts, Product and Engineering teams, business functions, and company leadership. Your mandate is to make FYUL's data ecosystem a trusted foundation for decision-making, self-service analytics, operational products, and AI-enabled experiences.
Key responsibilities include:
**Strategy & Vision**: Define a multi-year product vision and strategy aligned with company priorities and AI ambitions. Understand the needs and workflows of data producers and consumers. Identify opportunities where shared data capabilities can unlock growth, efficiency, and better decision-making. Balance near-term user value with foundational investments for long-term scale.
**Discovery & Definition**: Turn fragmented stakeholder requests into clear, structured problem spaces. Identify highest-risk assumptions and sequence discovery before significant investment. Distinguish between needs requiring local solutions, reusable data products, platform capabilities, governance changes, or operating-model changes. Define clear outcomes, success measures, scope boundaries, dependencies, risks, adoption expectations, and decision gates.
**Portfolio & Roadmap**: Build an outcome-based portfolio covering governed data products, metric definitions, semantic-layer capabilities, data discovery and metadata, self-service analytics, data quality and observability, secure access for applications and AI agents, and AI quality gates. Clarify which capabilities belong in the shared platform versus domain-owned. Create coherent cross-team plans with clear ownership, sequencing, and dependencies.
**Prioritization & Execution**: Prioritize across platform foundations, governance, self-service, AI enablement, reliability, cost efficiency, and domain needs. Make opportunity costs and trade-offs explicit. Protect high-leverage foundational work from losing priority to short-term requests. Partner with Data and Engineering leadership on resourcing and build-versus-buy decisions. Unblock systemic constraints.
**Outcomes & Measurement**: Define a North Star Metric and supporting KPI tree. Establish baselines and targets before major investments. Measure both direct platform outcomes and enabled business value. Communicate progress, risks, and outcomes to senior stakeholders.
**Governance & Alignment**: Partner with business owners, Analytics, Data Engineering, and Security to create scalable governance mechanisms. Ensure important metrics and data products have clear definitions, owners, documentation, and quality standards. Align senior stakeholders around goals, priorities, and trade-offs. Translate complex data and technology topics into clear business decisions.
**Product Maturity**: Establish strong product-management standards for platform and data-product work. Coach Product Managers on discovery, prioritization, outcome definition, and post-launch evaluation. Create reusable practices and decision frameworks. Share insights and learnings across the organization.
Required qualifications: Proven record of delivering substantial impact through complex platform, data, infrastructure, or enterprise products. Experience owning strategy and outcomes across multiple teams or domains without formal authority. Ability to turn highly ambiguous and technical problems into clear strategies and executable plans. Strong understanding of data platforms, data models, warehouses, semantic layers, BI, governance, metadata, data quality, access control, and AI-enabled analytics. Sufficient technical fluency to engage credibly in architecture and engineering trade-offs. Strong commercial and analytical judgment. Excellent written and verbal communication. Experience aligning senior stakeholders around difficult priorities and trade-offs. Experience coaching Product Managers or improving product practices at organizational scale.
