Leads strategy, roadmaps, governance, and execution for enterprise data products supporting analytics, reporting, financial insights, customer intelligence, and AI/ML. Partners with Product, Data Engineering, Analytics, and business leaders to define scalable data models, semantic layers, data contracts, quality standards, and self-service analytics guardrails. Prioritizes business value while strengthening platform scalability and enabling trusted AI-ready data foundations.
About the Role
We are seeking a Group Technical Product Owner to lead a portfolio of enterprise data products that power analytics, operational reporting, financial insights, customer intelligence, and AI/ML use cases across the organization.
This role sits at the intersection of Product, Data Engineering, and the Business. You will own data product roadmaps, define governed data models, and ensure our modern data platform delivers measurable business outcomes — not just dashboards.
You will operate at a portfolio level, driving reusable, scalable data products across domains such as:
- Financial & revenue reporting
- Sales & customer performance
- Asset & transactional data
- Behavioral / clickstream data
- Operational metrics
- This is a strategic role focused on building trusted, AI-ready, enterprise data foundations.
What You’ll Do
- Own Data Product Strategy & Roadmaps
- Define and manage roadmaps for a portfolio of enterprise data products.
- Translate business problems into scalable, reusable data models.
- Ruthlessly prioritize based on business value, architectural integrity, and long-term platform health.
- Drive alignment across Product, Engineering, Analytics, and Business leaders.
- Lead Technical Data Product Execution
- Partner with Data Engineering to design governed data models, pipelines, and semantic layers.
- Own backlog refinement and acceptance criteria for data product increments.
- Ensure consistent metric definitions, lineage, and data quality standards.
- Balance short-term reporting needs with long-term scalability.
- Establish Governance & Self-Serve Guardrails
- Drive adoption of a governed semantic layer as the source of truth for enterprise KPIs.
- Reduce metric duplication and fragmented reporting logic.
- Enable self-service analytics within structured guardrails.
- Define and enforce data contracts and standards across domains.
- Enable AI & Advanced Use Cases
- Ensure data products are structured to support personalization, predictive models, and AI/LLM initiatives.
- Partner with analytics and data science teams to provide high-quality, reusable inputs.
- Promote an AI-ready data ecosystem through strong modeling and governance.
What You Bring:
Data & Platform Expertise
- 5+ years in Technical Product Ownership, Data Product Management, or similar roles.
- Experience with modern cloud data platforms (e.g., Snowflake, BigQuery, Redshift, Azure Synapse).
- Strong understanding of dimensional modeling, domain modeling, and metric governance.
- Experience working with BI and semantic layer tools (e.g., Looker, Tableau, Power BI, dbt).
Product & Business Mindset
- Experience owning roadmaps and prioritizing based on measurable business impact.
- Ability to frame problems clearly and define value hypotheses.
- Strong stakeholder management across technical and business audiences.
- Comfort navigating ambiguity and driving clarity.
Leadership
- Experience mentoring junior product owners or analysts.
- Strong communicator able to explain trade-offs between speed, quality, and scalability. Ability to influence without formal authority.
What Success Looks Like Within 12 months, you will have:
- Established governed, reusable data products across key business domains.
- Reduced metric duplication and inconsistent reporting.
- Improved dashboard and reporting delivery velocity.
- Enabled trusted self-service analytics.
- Strengthened the foundation for AI and advanced analytics initiatives.
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