Lead Data Engineer

About the role

About BEES

Join us to build the future of B2B commerce!

BEES is AB InBev’s B2B platform. Through our ecosystem, merchants and retailers across 29 countries can stock their businesses quickly, easily, and securely. At BEES, we dream big, lead with purpose, and develop technology that transforms the way retailers and sellers grow.

Every line of code and every partnership is built in service of a single mission: to make commerce better for retailers and sellers around the world. Here, your work is not just important. It makes a difference!

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 experience mentoring engineers and providing technical leadership across multiple teams;

- Ability to evaluate architectural trade-offs, identify long-term risks, and design solutions aligned with business growth objectives;

- Experience working in highly scalable and mission-critical environments.

More about you:

- Serve as the primary technical reference for Data Engineering and Data Platform initiatives;