Director, Data and Analytics, Governance and Innovation

Summary: As part of the LATAM Data & Analytics team, you will lead the data governance and innovation agenda that makes our data trusted, connected and AI-ready — the foundation the business needs to run on connected intelligence rather than isolated reports. You will define and operate the standards, roles and controls that keep data reliable across our Consumer, Customer and Enterprise domains, and you will bring in new practices, tools and AI capabilities that raise the quality and value of what we deliver.   This is a hands-on leadership role with two connected mandates. On governance, you own data quality, master and metadata management, lineage, classification,   privacy   and Responsible-AI controls, so trusted data and safe AI agents are possible at scale.   On innovation , you pilot and scale new capabilities — governed self-serve, AI-Ready datasets , agentic use   cases — and help embed them into everyday ways of working. You are the enterprise-data voice in the AI LATAM Office and a guardian of “one governance” across Data & AI initiatives.   You will contribute to the broader data strategy and LRP 2030 vision, but your primary accountability is making that vision trustworthy and executable through strong governance and practical innovation — not owning the end-to-end strategy or investment roadmap, which sits with the D&A leadership team.   What   You’ll   Do for Us   Data Governance & Trust (core)   Operate the “one governance” model   day to day — a shared   Business   +   GDN   framework with clear RACI, stewardship, decision   rights   and regular backlog/priority reviews across Data & AI LATAM initiatives.   Own enterprise data standards   for data quality, master/reference data alignment, business glossary, data contracts with bottlers,   classification   and access — certified once and reused across products and experiences.   Manage metadata,   catalog   and end-to-end lineage   (Purview 2.0), so governed data is easy to find, trusted and traceable from source to decision — the prerequisite for reliable AI agents.   Run data-quality operations   — anomaly detection, DQ   in dexes , issue   triage   and remediation with data stewards and   DataOps , keeping our critical datasets healthy.   Safeguard privacy,   security   and compliance   (LGPD/GDPR and local regulation, RBAC/ABAC, sensitivity classification), embedding controls into platforms and   aligning with   enterprise cyber and emerging AI-regulation standards.   Innovation & AI Enablement   Champion AI-ready foundations   — apply and evolve the AI-Ready Dataset guidelines, and support initiative certification and T1/T2/T3 scoring (scalability, operability, maintainability) in the AI LATAM Office.   Embed Responsible AI in practice   — fairness,   bias   and model/agent-drift checks, plus lineage and auditability for AI use cases, so agents inherit the governance of the data they read.   Pilot and scale new capabilities   on the target stack (Microsoft Fabric/ OneLake , MDM, Purview 2.0, agentic/ Foundry) —   turning proofs of concept into governed, reusable patterns.   Enable governed self-serve   (BYOD / self-serve reporting), so power users and business SPOCs generate insights without adding fragmentation or losing quality.   Adoption, Advisory & Team   Act as trusted advisor and   enterprise-data   SME   across workstreams — helping Strategy, Franchise, Commercial and Marketing understand what data we have, how it is governed, and how to use it well.   Drive adoption and data literacy   through the Data Community of Practice, AI upskilling and clear documentation,   standards   and playbooks.   Lead and grow a multidisciplinary team   (data governance, data stewards, and product/engineering partners),   building   capability and a healthy, engaged culture across seniority levels.   Partner   across the ecosystem   — Global