Profile

- Minimum 3 years of experience in product management | product ownership.
- Minimum 1 year of solid hands-on experience with data products, data platforms or analytics products.
- Working knowledge of lakehouse | medallion architecture, data modelling and data quality concepts.
- At least 1 year of hands-on exposure to Azure data services including Azure Databricks, ADLS, Synapse and Unity Catalog.
- Familiarity with MCP (Model Context Protocol) and how AI agents consume data and tools is highly preferredUnderstanding of GenAI use cases and the data they require; hands-on GenAI product experience is preferable.
- Comfortable producing PRDs, user stories, acceptance criteria, KPIs and release plans in Azure DevOps.
- Experience having delivered data products end-to-end is mandatory (and must be shared during interview)Excellent communication skills in English.

Responsabilities

- Own the definition, planning and delivery of data products – from discovery through release and lifecycle management.




- Define and manage products that expose certified data and functions to applications and AI agents through MCP.
- Translate business goals and discovery insights into product requirements, user stories, acceptance criteria and release plans.
- Define data product contracts: ownership, grain, quality SLAs, naming conventions, lineage and source-change handling.
- Work with the Azure platform and components running on it – ADLS, Delta Lake | Databricks, Synapse, Unity Catalog.
- Coordinate cross-functional execution with business, data engineering, architecture, security and compliance.
- Think in terms of reusable products and components (not only in one project but across projects)
- Add | Manage | Document project user stories to Azure Boards.
- Validate outcomes with data – adoption, quality and usage KPIs – and follow Responsible AI and compliance guidelines.

📌 Data Product Manager | Data & AI (Ciudad de México)
🏢 Empresa Confidencial
📍 Ciudad de México