Product Owner - Data Acceleration

Role Overview

We are seeking an experienced Product Owner / Business Lead to drive the delivery of a strategic Data Acceleration Program (DAP) focused on building and leveraging a modern Data Lakehouse / Data Backbone within the Life Insurance and Investments industry.

The role will lead the Client & Marketing workstream, translating business strategy and user needs into an executable product roadmap and prioritized backlog. The successful candidate will work across business and technical squads, partnering with Product Managers, data teams, business stakeholders, data scientists, insights specialists, campaign owners, and senior leadership to deliver data and analytics products that improve customer experience, marketing effectiveness, and data-driven decision-making.

This is a highly collaborative business-and-technology product role, requiring strong product ownership, data literacy, stakeholder management, and Agile delivery experience.

Key Responsibilities

Product Ownership & Roadmap

Partner with the Product Manager to translate the Data Backbone vision into an executable product roadmap.

Own execution of the Client & Marketing Data Backbone workstream.

Translate business requirements into actionable product backlog items, epics, and user stories.

Prioritize features and capabilities based on business value, user needs, dependencies, and organizational priorities.

Consolidate and harmonize requirements from multiple business stakeholders and data consumers.

Guide business and technical squad members and proactively remove delivery blockers.

Champion an Agile, collaborative, and outcome-driven product delivery environment.

Data Product & Business Value

Ensure Data Backbone capabilities effectively address the needs of data scientists, insights specialists, campaign owners, operations teams, and other end users.

Define and track product OKRs and success metrics.

Contribute to business cases and Value Statement Cards (VSCs) for Data Backbone initiatives.

Quantify expected business benefits and potential value associated with product features and use cases.

Drive value realization, adoption, and utilization of deployed data capabilities.

Identify opportunities for cost savings, capacity improvement, system/report decommissioning, and enhanced customer or marketing initiatives.

KPI & Business Logic Stewardship

Drive standardization and alignment of business logic, metrics, and KPI definitions across functions, Lines of Business, and markets.

Ensure KPI definitions are aligned with business objectives and intended business outcomes.

Coordinate KPI validation and endorsement with KPI Owners and Executive Leaders.

Promote consistent use of trusted data and standardized metrics across business stakeholders.

Stakeholder & Leadership Management

Act as a key business interface between Client, Marketing, Data, Technology, Finance, Change Management, and Training teams.

Facilitate senior leadership discussions and provide visibility into product progress, risks, priorities, and value realization.

Build stakeholder confidence and alignment around Data Backbone capabilities and roadmap.

Educate business and technical users on Data Backbone concepts, capabilities, and use cases.

Partner with Change Management and Training teams to drive adoption of dashboards, reports, data products, and data warehouse capabilities.

Agile Delivery

Champion Agile practices across the product squad.

Facilitate or actively participate in sprint planning, backlog refinement, sprint reviews, and retrospectives.

Maintain healthy and prioritized backlogs aligned with business outcomes.

Monitor delivery commitments, dependencies, quality, and timelines.

Ensure requirements are clearly defined and actionable for technical delivery teams.

User Experience & Continuous Improvement

Understand the needs and pain points of data consumers and business users.

Gather user feedback and translate insights into product improvements.

Monitor product usage, adoption, and effectiveness.

Identify opportunities to improve self-service analytics, data accessibility, and user productivity.

Risk & Delivery Management

Proactively identify and assess product, delivery, data, and stakeholder risks.

Develop mitigation and contingency plans for identified risks and issues.

Escalate critical blockers appropriately and drive resolution across relevant teams.

Required Qualifications & Experience

Bachelor's degree in Computer Science, Information Systems, Business, or a related field; Master's degree is preferred.

5+ years of experience as a Product Owner, Business Lead, or equivalent product/business role supporting data-driven initiatives.

Proven experience translating business requirements into product roadmaps, backlogs, epics, and user stories.

Strong understanding of data management, analytics, data products, and modern data/lakehouse architectures.

Demonstrated experience delivering products or solutions through Agile, Lean Incremental, and/or Waterfall methodologies.

Strong experience managing multiple business and technical stakeholders.

Excellent analytical, problem-solving, communication, and presentation skills.

Demonstrated ability to work with and influence senior stakeholders and cross-functional teams.

Strongly Preferred Experience

Experience in Life Insurance, Insurance, Investments, Financial Services, or related regulated industries.

Experience delivering data analytics products for Client Experience, Customer Analytics, Marketing, Campaign Management, or Customer Insights.

Experience working with Data Lakehouse / Data Backbone / Modern Data Platform initiatives.

Experience defining and standardizing business KPIs, metrics, and business logic.

Experience driving adoption and measurable business value from data products.

Experience managing or working within cross-functional Agile squads consisting of business and technical resources.

Technology / Tools

Candidates should ideally have exposure to:

JIRA – product backlog, user stories, sprint and delivery management

Confluence – product and requirements documentation

AWS – cloud/data platform exposure

Tableau – analytics and visualization

Erwin Data Modeler – data modeling concepts

Modern Data Lakehouse / Data Warehouse architectures

Data analytics, data governance, and data product concepts