Product Owner Data
Technical skills
- Product ownership and Agile methodologies (Scrum, SAFe).
- Data platforms, data warehouses, and data ecosystems.
- Data governance, data quality, and data management principles.
- Business intelligence and analytics tools (Power BI, Tableau, Looker).
- SQL and data querying fundamentals.
- User story writing and backlog management.
- Product management tools (Jira, Confluence, Azure DevOps).
- KPI definition and performance measurement.
- Data modeling and analytics concepts.
- Understanding of cloud-based data platforms (Azure, AWS, GCP).
Soft skills
- Strong stakeholder management and communication skills.
- Strategic thinking and business acumen.
- Analytical and data-driven decision-making.
- Leadership and influence without direct authority.
- Prioritization and organizational skills.
- Problem-solving and critical thinking.
- Adaptability and change management capabilities.
- Collaboration and teamwork mindset.
- Career Opportunities
- CTA to the offer
The Data Product Owner is responsible for defining and driving the vision, strategy, and delivery of data products that create business value. Acting as the link between business stakeholders, data teams, and technical experts, they ensure that data solutions meet user needs while aligning with organizational objectives and data governance standards.
Main activities
- Define and communicate the vision, roadmap, and objectives of data products.
- Gather, prioritize, and manage business requirements and user needs.
- Maintain and prioritize the product backlog based on business value and strategic goals.
- Collaborate with Data Engineers, Data Analysts, Data Scientists, and business stakeholders.
- Translate business needs into clear user stories and functional requirements.
- Lead Agile ceremonies and support delivery teams throughout the product lifecycle.
- Monitor product performance through KPIs and data-driven insights.
- Ensure alignment with data governance, quality, security, and compliance requirements.
- Drive continuous improvement and adoption of data products across the organization.
Application form
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