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.
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.
Drive adoption of a governed semantic layer as the source of truth for enterprise KPIs.
Enable self-service analytics within structured guardrails.
Ensure data products are structured to support personalization, predictive models, and AI/LLM initiatives.

Requirements

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).

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data modelingdimensional modelingmetric governancebacklog refinementdata quality standardspredictive modelsAILLM

Soft Skills

prioritizationalignmentpartnershipcommunication