1 month ago
Campinas, BrazilStaff+
Responsibilities
- Develop and operationalize the strategic roadmap for the data platform.
- Build and evolve Lakehouse, ETL, streaming, MDM, data quality, governance, and scalable data platform capabilities.
- Lead modernization programs and delivery of reusable data products and platform services.
- Collaborate with engineering teams across design, development, testing, deployment, and production support.
- Optimize platforms, reduce technical debt, and promote modern data engineering practices.
- Serve as the primary technical reference for Data Engineering and Data Platform initiatives.
- Mentor engineers through technical coaching, architecture reviews, and best-practice guidance.
- Define engineering standards for architecture, code quality, testing, reliability, maintainability, and production readiness.
- Align teams on platform standards, architecture, and long-term technical direction.
- Balance strategic planning with hands-on execution on critical implementations.
Requirements
- Degree in Computer Science, Computer Engineering, Information Systems, Systems Development Analysis, or a related field.
- Advanced English proficiency.
- 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, entity resolution, matching and survivorship strategies, and data governance.
- 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, 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 align solutions with business growth objectives.
- Experience working in highly scalable and mission-critical environments.
- Preferred experience leading enterprise-scale Data Engineering and MDM transformation initiatives.
- Preferred experience defining multi-year technology roadmaps and platform modernization strategies.
- Preferred hands-on experience transitioning batch architectures to streaming solutions.
- Preferred experience with multi-region, multi-brand, or highly regulated data environments.
- Preferred understanding of data product architecture and domain-oriented data design.
- Preferred experience influencing executive stakeholders and driving strategic technology decisions.
- Preferred significant experience building and operating business-critical, high-scale data platforms.
Benefits
- Performance-based bonus, attendance bonus, private pension plan, meal allowance, days off, and transport allowance, subject to applicable rules.
- Health, dental, and life insurance; medicine discounts; WellHub partnership; and childcare subsidies.
- Discounts on Ambev products and Clube Ben partnership.
- Scholarship, school materials assurance, and language and training platforms.
- Casual office and dress code.
- Equal Opportunity and Affirmative Action employer.
- Advanced English is required; the posting does not specify a remote or hybrid work arrangement.
Tech Stack
Categories
Data Engineering
About BEES
BEES builds a B2B digital commerce and marketplace platform for small and medium retailers to order products, manage invoices, and track deliveries from AB InBev and partner suppliers. The business supports online ordering, promotions, and data-driven sales tools across 29 countries. Created by and owned by AB InBev, BEES is headquartered in Rotkreuz, Zug, and focuses on digitizing distributor-to-retailer workflows in beverage and adjacent categories.