Data Product Owner

• Discover and map the “AS-IS” status of business teams, including their current analytic solutions and data rituals
• Frame the “TO-BE” business problems , understanding key decisions, use cases, and summarizing the business team's data maturity
• Identify project stakeholders and Data Champions, and define the required product solution type (Self-Service, Enterprise BI, AI solution)

2. Detailed Data Assessment

• Assess granular data needs : sources, required granularity, frequency, dimensions of analysis, and calculation logic for KPIs
• Identify access, visibility, and privacy rules for sensitive data
• Assess basic quality expectations (freshness, completeness, accuracy) and perform preliminary QA on data availability

3. Data Modeling & Prototyping

• Understand existing AS-IS semantic models and their use cases
• Propose conceptual and simplified logical / physical data modeling to bridge the gap before engineering implementation
• Define the user journey , build mock-up proposals, and validate them directly with business stakeholders

4. Backlog Management & Delivery Strategy

• Consolidate all needs into a manageable backlog , confirming Epics and writing detailed User Stories
• Prioritize delivery based on business value , aligning with PI Planning timelines
• Functional Squad Leadership : act as the daily operational leader for technical delivery squad, animating Agile rituals and guiding their execution

5. Release, UAT & Enablement

• Validate developed solutions internally and orchestrate formal business UAT sessions
• Communicate releases directly to the business audience
• Train users — post-release demos, recorded functionality showcases — and provide comprehensive documentation

6. Adoption Measurement & Continuous Improvement

• Define & track adoption metrics : monitor quantitative usage post-release to assess true penetration within the business team
• Measure business impact : evaluate realized value against the initial “TO-BE” framing (e.g. time saved in reporting, revenue uplift from a pricing model, error reduction in supply chain forecasting)
• Build systematic feedback loops : establish qualitative mechanisms to identify friction points and capture evolving needs (e.g. satisfaction surveys, quarterly shadowing sessions, open office hours)
• Feed the backlog iteratively : translate operational feedback and user requests into prioritized tickets to continuously improve the data product's reliability and feature set
• 4-6 years of experience as Data Product Owner, Data Product Manager, or in a similar product-facing data role
• Proven track record owning data products end to end — from business discovery and framing through delivery, UAT, and post-release adoption
• Experience running discovery with business teams and translating ambiguous needs into Epics and User Stories
• Experience working inside an Agile / PI Planning delivery model