Senior Data Engineer

<p><span style="font-size: 12pt;"><strong>About us</strong></span></p> <p>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.</p> <p><span style="font-size: 12pt;"><strong>About BEES</strong></span></p> <p>At BEES, our ambition is – and always will be – to put customers at the heart of everything we do, making their lives easier and their businesses more profitable. Through our B2B e-commerce and SaaS platform, we bring the power of digital to small and medium-sized retailers, unlocking new growth opportunities for all.</p> <p><strong>What you'll do:</strong></p> <ul> <li>Leads efforts within the organization to drive the development and maintenance of data services and solutions to support products, downstream services, or infrastructure tools and platforms used across BEES.</li> <li>Design efficient data models and understand concepts such as normalization, denormalization, and dimensional modeling.</li> <li>Implement improvements in architecture and processes to improve the performance, monitoring, and evolution of data products.</li> <li>Develop and maintain data ingestion, processing, control/security, and data provisioning processes for different consumers (services, front-end, among others).</li> <li>Contribute to obtaining knowledge in the business context and creating new data products to meet their strategic and operational needs.</li> </ul> <p><strong>What you'll need:</strong></p> <ul> <li>Degree in Computer Science, Computer Engineering, Information Systems, Systems Development Analysis or similar;</li> <li>Advanced English;</li> <li>Assess scalability, reliability, security, and compliance implications of data pipeline designs.</li> <li>Understand cloud computing platforms and services offered by providers like AWS, Azure, and Google Cloud.</li> <li>Evaluate programming solutions in Python, PySpark, Scala, and SQL for data processing and analysis.</li> <li>Evaluate data quality processes and controls to ensure accuracy and completeness.</li> <li>Apply debugging techniques to identify and resolve cross-module issues.</li> <li>Implement monitoring, alerting, and failure handling mechanisms in architecture designs.</li> <li>Assess effectiveness of CI/CD principles and practices in automated pipelines.</li> <li>Design, develop, and maintain APIs for data exchange between applications.</li> <li>Apply Agile practices to plan, execute, and deliver data engineering tasks and projects.</li> <li>Logical reasoning and analytical skills;</li> <li>Meeting deadlines and quality of work;</li> <li>Effective and transparent dialog with other areas and co-workers;</li> <li>Ability to communicate and interpersonal relationships to to present cases and discuss them with other areas involved;</li> <li>Being independent in activities;</li> <li>Work as part of a team, promoting a good relationship with the team;</li> <li>Evaluate data pipeline solutions for latency, throughput and accuracy.</li> <li>Analyze data requirements and business needs to inform data modeling decisions.</li> <li>Understand the principles and assumptions of different machine learning capabilities.</li> <li>Integrate data sets with visualization tools to create insightful reports and dashboards</li> </ul> <p><span data-teams="true"><strong>More about you:</strong></spa