Senior Product Manager, Data

This is a fully remote position, open to applicants in Latin America.

📋 Description

• Lead discovery initiatives by collaborating with both business and technical stakeholders through interactive sessions, identifying current data usage, and transforming insights into prioritized use cases and requirements.

• Take ownership of definitions by pinpointing inconsistent metrics and business terminology, while driving the establishment of agreed-upon documented definitions with accountable stakeholders.

• Facilitate business-wide adoption and secure sponsorship and alignment from leadership.

• Implement a hypothesis-driven approach by validating client assumptions through sessions or experiments, and documenting clear conclusions and rationales.

• Collaborate with the Solution Architect to define scope, acceptance criteria, and vertical-slice order based on value and risk, thereby shaping increments.

• Evaluate technical decisions from a business perspective and provide constructive feedback on unsuitable data models, definitions, or trade-offs.

• Maintain regular communication with the Project Manager by tracking decisions, open questions, risks, and stakeholder commitments.

• Facilitate the transfer of ownership through well-defined processes, documentation, and an ownership model that ensures the layer remains accurate post-engagement.

⛳️ Requirements

• A minimum of 5 years in product management, particularly with data products (such as analytics, data platforms, metrics or semantic layers, internal data tools, or similar).

• Proven experience in aligning stakeholders across various business areas on shared definitions, priorities, and operational methodologies.

• A structured and evidence-based approach to discovery and prioritization.

• Ability to make informed decisions with limited information and effectively manage senior stakeholders.

• A successful track record of ensuring product adoption rather than mere delivery.

• Experience in defining, designing, and delivering AI or LLM-based products.

• Proficient in written and spoken English.

• Sufficient technical knowledge to question data architects and engineers on technical definitions, modeling choices, and trade-offs, as well as comprehend their responses (strong advantage).

• Familiarity with modern data stacks, such as Databricks, Snowflake, dbt, data catalogs, or governance tools (strong advantage).

🏝️ Benefits

• Monthly USD Service Fee

• 20 business days of paid Agreed Time Off—Annual + 6 Local Holidays

• Caregiver Time Off

• A dynamic remote work culture, allowing you to work from anywhere!

• An entrepreneurial environment.