Product Owner II - Data
Experity (company site, opens in a new tab)4+ yrsBengaluruOn-siteDirect career pageEst. 12–22 LPA
Posted 1d ago
Reach people at Experity
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Experity you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Own end-to-end execution of assigned data and analytics product roadmap priorities from discovery through delivery and adoption.
- Translate data strategy, customer needs, and business priorities into clear, prioritized backlog items with defined acceptance criteria and business rules.
- Coordinate across Product, Data Engineering, Analytics, Architecture, and business teams across time zones ensuring clear communication, decision tracking, and delivery progress.
Minimum Requirements
- Bachelor's degree in Business, Information Systems, Computer Science, Data Analytics, Engineering, or related field, or equivalent experience.
- 4+ years of experience in product ownership, product analysis, business analysis, or data products/analytics roles.
- Strong analytical skills including working knowledge of SQL and ability to validate datasets and requirements.
- Experience working across Product, Data Engineering, Analytics, Architecture, QA, and business teams on data or analytics products.
Ideal Candidate Profile
- Experienced in managing data products or analytics capabilities with strong ownership of backlog quality and prioritization.
- Capable of bridging technical and non-technical stakeholders with clear communication and documentation skills across distributed and multidisciplinary teams.
- Familiar with modern data concepts (data models, data quality, metric logic) and data platform technologies such as Snowflake or BI tools like Tableau or Power BI (preferred but not mandatory).