Data Engineering Manager

Job Purpose:
• The Data Engineering Manager is crucial within the D&T department at HEINEKEN International, spearheading the APAC Data & Analytics Hub. It is central to operationalizing our strategy of establishing standardized and scalable data foundations across the region and enterprise. Renowned for delivering cutting-edge innovation, robust technology, and advanced analytics, the D&T department equips HEINEKEN with a significant technological advantage, aligning with our ambitious organizational goals.
• The role holder will work with colleagues across Heineken as part of a team that structure the entire process of data extraction, transformation, and storage using serverless Azure services to deploy models and analytical solutions for the enterprise within a specific Function or a group of Functions.
• It is essential that the role holder can manage quality assurance, data migration and integration, and solution deployment to ensure the business gets the best value. This will be achieved by building strong relationships and collaboration with members of the broader HEINEKEN data organisation as well as various programs across the central, regional and Operating Company (OpCo) structures.
• In particular, he/she will partner with a growing group of data professionals such as Data Scientists, Machine Learning Engineers and Product Managers who play a crucial role in the development and delivery of Analytics products at scale.
Key Responsibilities:
• Structure end-to-end processes of data extraction, transformation, and storage to deploy models and analytical solutions in real-time and offline analytic processing.
• Handle activities such as quality assurance, data migration and integration, and solution deployment to ensure the business gets the best value.
• Implement, maintain, and further develop ETL processes, data lineage, and observability across large-scale data ingestion from a variety of sources
• Design and implement data flows to ensure efficient and reliable data movement (e.g. unit and integration tests).
• Provide technical support in understanding business problems and designing smart data products.
• Collaborate within an agile culture, contributing to the team's success.
• Relationship creation and management of broader team's stakeholders to ensure strong connection and collaboration for team)
• Continued self-development and research of best-in-class analytical approached
• Management and/or development and capability building of Junior/Senior Data Engineers (team of 7)
• Potential responsibility for selection of AA Vendors and AA Tooling workbench (Procurement & Enablement of tools sits with GIS)