Product Owner... (Ciudad de México)

Databricks Product Owner Remote opportunity but must be able to travel to NYC for workshops. Role Overview The Databricks Product Owner will lead the product vision and delivery of the Groupe Data Foundations Platform, a mission-critical data catalogue built on Databricks that enables agentic AI development across our client Groupe. This role bridges business strategy, agency needs, and technical implementation to deliver federated, governed access to multimodal data assets for CoreAI and agency teams. You will own the product roadmap from discovery through delivery, working closely with the Databricks Architect and engineering teams to translate complex stakeholder requirements into actionable technical specifications while ensuring strict governance, privacy compliance, and alignment with Groupe standards. Key Responsibilities Product Strategy & Vision - Define and communicate product vision for the Data Foundations Platform aligned with CoreAI integration requirements and Groupe strategic objectives - Lead discovery workshops with agency stakeholders, Core Platform teams, and Resources to gather requirements and validate use cases - Develop and maintain product roadmap with clear prioritization across 11 implementation phases and 6 parallel workstreams - Translate business needs into user stories, acceptance criteria, and technical specifications for engineering teams - Own success criteria definition and measurement : ≥80% data source coverage,

0.85 Governance & Compliance Leadership - Design and implement comprehensive governance frameworks including tagging standards (data_classification, pii, retention_policy, legal_basis, data_origin) - Define data classification policies and ensure adherence to client / vendor license agreements at dataset level - Collaborate with Security Engineer to establish RBAC / ABAC policies and Unity Catalog governance structures - Coordinate with Re : sources on access control workflows, cross-charging mechanisms, and self-service admin portal requirements - Ensure compliance with GDPR, CCPA, and data residency requirements across all data assets - Validate audit logging, lineage tracking, and governance enforcement mechanisms Taxonomy & Ontology Design - Lead taxonomy design workshops to define core entities : Brand, Product, Campaign, Creative, Channel, Platform, Geo, Audience, KPI / Metric, Vendor, Person, Org - Establish entity relationships and ontology standards in collaboration with Information Architect and Databricks Architect - Define naming conventions (snake_case, client_region prefixes) and metadata schemas - Work with agency practitioners to configure client-specific taxonomy definitions through Core taxonomy applications - Ensure taxonomy integration with media performance data catalog and semantic layer Stakeholder Management - Serve as primary liaison between agency teams, Core Platform, Re : sources, and technical implementation teams - Facilitate regular stakeholder reviews, demos, and feedback sessions throughout delivery lifecycle - Manage expectations across federated agency teams and coordinate multi-client rollout strategy - Present progress, risks, and decisions to executive leadership and steering committees - Support change management and adoption strategy for agency practitioners Product Delivery & Execution - Manage product backlog with clear prioritization based on business value, technical dependencies, and risk mitigation - Lead sprint planning, backlog refinement, and retrospectives with cross-functional engineering team - Make real-time prioritization decisions across parallel workstreams (Foundation & Governance, Ingestion & Curation, Embeddings & Knowledge Graph, Retrieval & Evaluation, Operations & MCP, Testing & Validation) - Define configuration options for admin portal : data source selection, masking policies, taxonomy inheritance, access controls, workspace enablement - Validate deliverables against acceptance criteria and coordinate UAT activities Risk Management & Issue Resolution - Identify and mitigate risks related to governance complexity, adoption challenges, and cross-functional dependencies - Coordinate with Re : Sources support team for day-to-day issue resolution and escalations - Monitor project health metrics and proactively address blockers affecting timeline or quality - Ensure alignment on non-goals (e.g., front-end application development, real-time streaming) Required Qualifications Experience - 7+ years of product management experience in data platforms, analytics, or enterprise software - 3+ years working with cloud data platforms (Databricks, Snowflake, or similar) and Unity Catalog - Proven track record delivering complex, multi-stakeholder data governance and cataloging solutions - Experience managing federated data access across multiple business units or clients - Background in media, advertising, or martech industries preferred Technical Knowledge - Deep understanding of data governance frameworks, privacy regulations (GDPR, CCPA), and compliance requirements - Familiarity with metadata management, taxonomy design, and ontology standards - Knowledge of data cataloging, lineage tracking, and RBAC / ABAC access control patterns - Understanding of vector databases, embeddings, and RAG (Retrieval-Augmented Generation) architectures - Experience with MLOps, model governance, and AI safety considerations Skills & Competencies - Expert stakeholder management and communication skills across technical and non-technical audiences - Strong analytical and problem-solving abilities with attention to detail - Ability to translate ambiguous business requirements into clear technical specifications - Experience facilitating workshops and leading cross-functional teams - Proficiency in agile methodologies and product management tools (Jira, Confluence, Aha!, etc.) - Excellent documentation skills for governance policies, product specifications, and user guidance Preferred Qualifications - Experience with Databricks Unity Catalog, Delta Lake, and Delta Sharing - Knowledge of Model Context Protocol (MCP) or similar federated AI frameworks - Familiarity with advertising data ecosystems (DMPs, CDPs, ad platforms, measurement) - Understanding of agentic AI architectures and LLM integration patterns - Certification in data governance (CDMP, DGSP) or product management (CSPO, CPO)

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