Líder de Business Intelligence y Arquitectura de Datos

About the role

Heineken Panamá is looking for a senior professional to lead the design, integration, governance and evolution of its commercial data architecture. The role will ensure a single source of trusted information, turning multiple internal and external data streams into automated, traceable and actionable insights that support commercial, operational and financial decision‑making.

Key responsibilities

• Design, develop and maintain a comprehensive commercial and sales data model, integrating internal and external sources.
• Map, document and govern data from SAP, Heilite, Nielsen, Dichter & Neira, SEM/SFA, PICOS, billing, inventory, cost and manual reporting systems.
• Define and manage master data, business rules, data dictionary, KPIs and corporate reporting standards.
• Lead the transition from Heilite to SAP, preserving historical data continuity and metric comparability.
• Create and maintain executive and operational dashboards in Power BI and other visualization tools.
• Automate reports and manual processes, reducing Excel dependency and promoting certified datasets.
• Implement data quality, traceability, update and security controls.
• Generate analyses linking sales performance, market share, pricing, promotions, costs, margins and investments.
• Support revenue‑management initiatives and prepare the data foundation for AI and advanced analytics use cases.

Required profile

• Degree in Engineering, Systems, Statistics, Mathematics, Economics, Finance, Business Administration, Data Science or related fields.
• Preferably holds specialisations, certifications or complementary training in Data Analytics, Business Intelligence, Data Engineering or Data Architecture.
• More than 4 years of experience in Business Intelligence, Data Analytics, Data Architecture, Data Engineering or similar roles, preferably in fast‑moving consumer goods, retail or analytical consulting.
• Advanced proficiency in English.

Required skills

• Power BI
• SAP
• Data Modeling
• Data Governance
• Data Architecture
• Data Engineering
• Data Analytics
• Artificial Intelligence
• Advanced Analytics