Jobs

Description

Technical Product Owner

Work schedule hours are from 8:30 a.m. to 5:00 p.m. eastern standard time.

Duration: 5 months with extentions

Technical Product Owner – Data & Analytics (Broker Modernization & Discovery Zone)

Position Summary

• We are seeking an experienced Technical Product Owner to lead delivery of strategic Data & Analytics initiatives supporting client's multi-year Broker Modernization program while serving as Product Owner for our Discovery Zone Data & Analytics delivery team.
• This role combines hands-on Product Ownership, enterprise data leadership, and governance stewardship.
• The Product Owner will help establish and scale trusted data assets, semantic layers, data contracts, and Master Data Management capabilities that enable consistent reporting, analytics, AI, and business decision-making across the enterprise.
• The Product Owner will play a critical role in connecting enterprise program objectives to data products, ensuring business requirements are translated into high-quality backlog items, aligned to target-state architecture, governed according to enterprise standards, and delivered through iterative Agile execution.

Key Responsibilities

Broker Modernization Program Leadership

• Partner closely with the Chief Product Manager and Broker Modernization leadership team to understand program vision, strategic objectives, delivery roadmaps, and business outcomes.
• Take ownership of Program Initiatives within the Portfolio Backlog and drive alignment between program objectives, product roadmaps, and delivery execution.
• Collaborate with Product Owners across multiple teams to align epics, features, dependencies, and delivery plans to broader Program Initiatives.
• Drive cross-team planning and execution to ensure successful delivery of planned Delivery Increments and measurable business outcomes.
• Identify risks, dependencies, data impacts, and governance considerations associated with Broker Modernization initiatives.

Discovery Zone Product Ownership

• Serve as Product Owner for the InfoNinjas Scrum Team, responsible for delivery of Discovery Zone, client's self-service reporting and analytics environment.
• Actively participate in all Agile ceremonies, including sprint planning, daily stand-ups, backlog refinement, retrospectives, and PI planning sessions.
• Own and prioritize team backlog, defining epics, features, user stories, acceptance criteria, and delivery sequencing.
• Work closely with business analysts, reporting leaders, and business stakeholders across GBS and other client organizations to understand reporting needs, business questions, and analytical requirements.
• Work collaboratively with developers, QA, and Scrum Master to ensure clarity, delivery, and continuous improvement.
• Translate business requirements into scalable data products and analysis-ready datasets.
• Facilitate backlog refinement, sprint planning, stakeholder reviews, and release planning activities.
• Ensure delivered datasets, reporting assets, and analytics capabilities meet business expectations and support effective decision making.
• Provide regular updates to stakeholders at various levels of the organization on team progress, challenges, and alignment to business objectives.

Data Product & Analytics Leadership

• Partner with Data Engineers, BI Developers, Data Architects, and Data Scientists to define and deliver scalable analytics solutions.
• Work closely with the BI Architect to ensure adherence to enterprise architecture standards, data modeling best practices, and reporting design principles.
• Define and maintain requirements for analysis-ready datasets, including business rules, KPI definitions, data quality expectations, and consumption requirements.
• Support analytics and AI enablement initiatives through delivery of trusted, governed data assets.
• Promote adoption and effective use of enterprise reporting and analytics capabilities.

Enterprise Data Product & Trusted Data Asset Strategy

• Define and evolve trusted, reusable data products that support enterprise reporting, analytics, and AI-enabled solutions.
• Partner with Data Architecture, Governance, and Engineering teams to establish semantic layers, business-friendly data definitions, KPI standards, and governed consumption models.
• Drive development of enterprise data contracts between upstream and downstream domains to improve reliability, traceability, and accountability across the data ecosystem.
• Support enterprise Master Data Management (MDM) and Golden Record initiatives to improve consistency of key business entities across Broker, Customer, Producer, and enterprise domains.
• Promote the creation and adoption of trusted data assets that reduce duplicate reporting logic and accelerate business access to reliable insights.
• Ensure analysis-ready datasets align with enterprise semantic models, business definitions, governance requirements, and approved KPI frameworks.

Data Governance, MDM & Data Stewardship

• Serve as a champion of enterprise data governance practices, trusted data asset development, and semantic consistency across reporting and analytics solutions.
• Partner with Data Governance, Data Council, and domain data owners to identify, prioritize, and resolve data quality issues.
• Drive alignment between business definitions, KPI frameworks, semantic layers, and certified reporting assets.
• Support Master Data Management (MDM), Golden Record, and data stewardship initiatives to improve consistency and trust in enterprise data.
• Establish feedback loops between reporting consumers, data stewards, and engineering teams to continuously improve data quality and usability.

Required Qualifications

• Product Ownership experience supporting Data & Analytics, Data Platform, Data Governance, or Enterprise Reporting initiatives.
• Experience managing product roadmaps, backlogs, epics, features, user stories, and Agile delivery teams.
• Strong understanding of enterprise data management concepts including:
• Data Governance
• Master Data Management (MDM)
• Data Quality
• Data Lineage
• Metadata Management
• Data Modeling
• Experience working with cloud data platforms and modern analytics ecosystems.
• Strong business analysis and system analysis skills, including requirements elicitation, source-to-target mapping, data transformation requirements, and KPI definition.
• Experience partnering with business stakeholders to translate analytical needs into scalable data products and reporting solutions.
• Ability to manage multiple concurrent initiatives while balancing strategic priorities and day-to-day delivery responsibilities.

Preferred Qualifications

• Experience implementing or supporting:
• Semantic Layers
• Trusted Data Assets
• Data Contracts
• Master Data Management (MDM)
• Golden Record Strategies
• KPI Governance Frameworks
• Experience building scalable analytics ecosystems that support reporting, self-service analytics, AI, and enterprise decision support.
• Experience establishing data product operating models that align governance, engineering, analytics, and business stakeholders.
• Financial Services, Insurance, Wealth Management, Broker, or Distribution domain experience.
• Experience supporting large-scale data modernization or transformation programs.
• Experience with Snowflake, Databricks, AWS, Azure, Power BI, Tableau, or similar enterprise analytics platforms.
• Experience supporting AI-enabled analytics, reporting, or data science initiatives.
• Experience operating within highly regulated environments requiring strong governance, traceability, and auditability.

Success Measures

Success in this role will be measured by:

• Delivery of Broker Modernization initiatives aligned to planned Delivery Increments.
• Adoption and utilization of Discovery Zone analytics capabilities.
• Growth and adoption of trusted, reusable data assets across business domains.
• Successful implementation of semantic consistency and KPI governance standards.
• Improvements in data quality, lineage, stewardship, and business trust in enterprise data.
• Reduction in duplicate reporting logic and improved reuse of certified analytics datasets.
• Business value delivered through reporting, analytics, and AI-enabled decision support capabilities.