THE ROLE

The Senior Manager, Data & Analytics Products owns a portfolio of enterprise-critical Tier 1 products from strategy and discovery through delivery, adoption, service performance, and value realization. The role connects executive and business priorities to product roadmaps and leads across product, data engineering, analytics, governance, architecture, security, operations, and business teams.
The ideal candidate is a data and analytics leader with strong product judgment: commercially grounded, technically fluent, practical in the application of AI, and skilled at aligning senior stakeholders and global delivery teams. Success requires the ability to make enterprise data trusted, analytics products useful, and complex strategic programs executable - without requiring hands-on engineering or model development.

WHAT YOU'LL DO

• Tier 1 insights product portfolio strategy. Own the vision, value proposition, target users, product criticality, investment priorities, outcome metrics, and multi-horizon roadmaps for the company's most important data and analytics products. Balance run, grow, and transform priorities across the portfolio. 
• Discovery and product lifecycle. Lead stakeholder interviews, user research, decision-journey and process analysis, and opportunity sizing. Translate important business questions into product requirements, priorities, roadmaps, success measures, and an ongoing improvement agenda.
• Product reliability and performance. Define business-critical expectations for accuracy, freshness, consistency, usability, adoption, and support. Partner with Data Engineering team on availability, incident response, and technical remediation while maintaining transparent product-health reporting.
• Trusted data and governance. Establish clear ownership, shared definitions, lineage, and quality expectations for each product. Partner with Data Governance, Security, Privacy, and IT to ensure access, retention, and control requirements are appropriately addressed.
• Advanced analytics and applied AI. Identify where predictive analytics, generative AI, intelligent decision support, or automation can improve a user outcome. Shape prototypes and scalable solutions with clear evaluation measures, monitoring, explainability, controls, and human oversight.
• Executive priorities and strategic execution. Act as a trusted execution partner to senior leaders. Translate priorities into product investments, workstreams, owners, milestones, and decision forums; manage risks and dependencies; and prepare concise business cases, executive updates, and recommendations.
• Adoption and value realization. Lead launch, enablement, communications, and stakeholder engagement. Build feedback loops and measure adoption, satisfaction, decision effectiveness, productivity, revenue, cost, and risk outcomes to demonstrate and improve product value.
• Team and delivery leadership. Lead and develop product managers, analysts, and program resources while creating shared accountability across data engineering, analytics, architecture, governance, business teams, and vendors. Resolve trade-offs and sustain predictable, high-quality delivery.

We are primarily an in-office environment and therefore, you will be expected to work from the {{OFFICE_LOCATION}} office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave.

WHAT YOU BRING

• 15+ years of progressive experience across data and analytics, data-product management, strategic program leadership, transformation, or closely related roles, including leadership of complex enterprise initiatives.
• Demonstrated ownership of enterprise-critical data, analytics, reporting, master-data, or AI products from strategy and business case through delivery, operations, adoption, and measurable impact.
• Strong product-management fundamentals across portfolio strategy, discovery, prioritization, roadmaps, stakeholder governance, product performance, adoption, experimentation, and value realization.
• Sufficient technical fluency to translate business needs and make informed trade-offs with Data Engineering, Architecture, Security, and platform teams. Hands-on engineering, architecture, or platform administration is not required.
• Applied AI fluency, including the ability to identify valuable use cases, assess data readiness and risk, shape user and control requirements, and validate adoption and outcomes in partnership with technical teams.
• Experience defining business expectations and measures for accuracy, freshness, usability, adoption, stakeholder satisfaction, and value, while partnering with technical owners on availability, service levels, and support models.
• Track record of leading multidisciplinary teams and influencing senior executives, business owners, technical leaders, and global partners through competing priorities, risks, dependencies, and decisions.
• Strong commercial, financial, written, verbal, and visual communication skills, including opportunity sizing, business cases, resource planning, executive reporting, and concise product storytelling

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