Senior Manager Data Engineer

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 BEES

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.

• →You will lead a team of data engineers to deliver world-class safety solutions
• →Partner with customer teams, help see opportunities, gather requirements, and lead a technology roadmap and vision for the team
• →Recruit, encourage, and grow a top-notch engineering team
• →Develop systems and software to bring world class safety to global BEES

• Degree in Computer Science, Computer Engineering, Information Systems, Systems Development Analysis or similar;
• Advanced English;
• Design and develop data pipeline architectures for advanced analytics, machine learning, and real-time data processing.
• Innovate techniques to optimize data pipeline performance, efficiency, and reliability.
• Understand cloud computing platforms and services offered by providers like AWS, Azure, and Google Cloud.
• Analyze design requirements and constraints to identify optimal solutions for data and software architecture.
• Design scalable, reliable, and performant systems that meet business needs based on architecture requirements.
• Apply data quality assessment techniques such as data profiling, cleansing, and validation to identify and correct data quality issues.
• Implement monitoring and logging architectures for visibility and analysis of system performance and security.
• Analyze CI/CD pipeline configurations and logs for issue diagnosis and optimization opportunities.

• Degree in Computer Science, Computer Engineering, Information Systems, Systems Development Analysis or similar;
• Advanced English;
• Design and develop data pipeline architectures for advanced analytics, machine learning, and real-time data processing.
• Innovate techniques to optimize data pipeline performance, efficiency, and reliability.
• Understand cloud computing platforms and services offered by providers like AWS, Azure, and Google Cloud.
• Analyze design requirements and constraints to identify optimal solutions for data and software architecture.
• Design scalable, reliable, and performant systems that meet business needs based on architecture requirements.
• Apply data quality assessment techniques such as data profiling, cleansing, and validation to identify and correct data quality issues.
• Implement monitoring and logging architectures for visibility and analysis of system performance and security.
• Analyze CI/CD pipeline configurations and logs for issue diagnosis and optimization opportunities.
• Python, SQL proficiency
• Test automation and quality engineering
• Version control and Git workflows
• Design patterns and reusable frameworks
• Batch and streaming architectures
• Data modeling (dimensional, Data Vault, semantic layers)
• Enterprise-scale ETL/ELT design
• Metadata and lineage management

• Hiring and talent development
• Coaching and mentoring engineers
• Set engineering standards and best practices
• Drive architecture decisions
• Build a culture of engineering excellence

• Significant experience building and operating critical high-scale systems
• Good software engineering methodology: meaningful and deeply rooted opinions about testing and code quality, ability to make sound quality/speed trade-offs
• Understand principles and assumptions of different machine learning capabilities.

ABI Growth Group is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon of race, color, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other applicable legally protected characteristics.

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Remember: your data will never be used as elimination criteria in selection processes. With them, ABI Growth Group is able to analyze diversity and reduce biases in selection processes. We want to contribute to changing this reality by being an inclusive company. 

 For more information: www.bees.com and www.abinbev.com