Lead Data Engineer

About us AB InBev is the leading global brewer and one of the world’s top 5 consumer product companies. With over 500 beer brands, we’re number one or two in many of the world’s top beer markets, including North America, Latin America, Europe, Asia, and Africa. About AB InBev Growth Group Created in 2022, the Growth Group unifies our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and Marketing teams. By bringing together global tech and commercial functions, the Growth Group allows us to fully leverage data and drive digital transformation and organic growth for AB InBev around the world. In addition to supporting well known global beer brands like Corona, Budweiser and Michelob Ultra, the Growth Group is home to a robust suite of digital products including our B2B digital commerce platform BEES, on-demand delivery services Ze Delivery and TaDa Delivery, and table top beer keg PerfectDraft. We are an exceptional team, focused on understanding and supporting consumer and customer needs, harnessing new technology, and scaling growth opportunities. What you'll do: Develop, implement, and operationalize the strategic roadmap for the data platform, translating long-term architectural vision into executable initiatives and measurable outcomes; Build and evolve Lakehouse, ETL, streaming, and MDM capabilities, lead modernization programs, and drive the delivery of scalable data products and platform services; Work closely with engineering teams throughout design, development, testing, deployment, and production support to ensure platform solutions meet performance, reliability, governance, and business requirements; Identify opportunities for platform optimization, reduce technical debt, and accelerate the adoption of modern data engineering practices across the organization. What you'll need: Degree in Computer Science, Computer Engineering, Information Systems, Systems Development Analysis, or related fields; Advanced English; Strong experience designing and implementing large-scale ETL and data platform architectures; Extensive experience with Databricks and modern Lakehouse architectures; Strong cloud experience with Azure, AWS, and/or Google Cloud Platform; Experience with Master Data Management (MDM), entity resolution, matching and survivorship strategies, and data governance principles; Deep understanding of data modeling, distributed data processing, orchestration frameworks, and data platform scalability; Experience designing data contracts, schema evolution strategies, and reusable data platform components; Strong software engineering fundamentals, including testing, CI/CD, code quality, observability, and operational excellence; Experience establishing data quality frameworks, validation layers, reconciliation processes, and reliability standards; Knowledge of streaming architectures, event-driven systems, and modern data integration patterns; Proven…