About the job
About AB InBev
AB InBev stands as the foremost global brewer and ranks among the top five consumer product companies worldwide. Boasting a diverse portfolio of over 500 beer brands, we are a leader in numerous key beer markets including North America, Latin America, Europe, Asia, and Africa.
About ABI Growth Group
Established in 2022, the ABI Growth Group integrates our business-to-business (B2B), direct-to-consumer (DTC), Sales & Distribution, and Marketing teams. By uniting global technology and commercial functions, the Growth Group empowers us to harness data effectively, driving digital transformation and organic growth across AB InBev globally.
About BEES
As a pivotal technology cell within our organization, our mission is clear: to grow. We aim to develop as individuals, professionals, and as a company. To realize this goal, we leverage technology to craft digital solutions that simplify our customers’ experiences, enhance their decision-making capabilities, and boost their business profitability. With locations in São Paulo and Campinas, we actively encourage our team to engage in major events and significant meetings throughout the year.
Responsibilities:
- Lead initiatives within the organization to drive the development and upkeep of data services and solutions that support various products, downstream services, or infrastructure tools and platforms utilized across BEES.
- Design streamlined data models and grasp essential concepts such as normalization, denormalization, and dimensional modeling.
- Implement architectural enhancements and process improvements to boost the performance, monitoring, and evolution of data products.
- Develop and maintain processes for data ingestion, processing, control/security, and provisioning for diverse consumers (services, front-end, etc.).
- Contribute towards understanding business contexts and developing new data products to address strategic and operational requirements.
Requirements and Qualifications:
- Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, Systems Development Analysis, or a related field.
- Proficient in English (advanced level).
- Ability to assess scalability, reliability, security, and compliance aspects of data pipeline designs.
- Familiarity with cloud computing platforms and services from providers like AWS, Azure, and Google Cloud.
- Experience with programming solutions in Python, PySpark, Scala, and SQL for data processing and analysis.
- Ability to evaluate data quality processes and controls to ensure data accuracy and completeness.
- Proven skills in debugging and troubleshooting.

