Ambev

Software Engineer

• Work on the development and evolution of backend solutions, from technical design through implementation and maintenance
• Participate in technical refinements, architecture discussions, and solution definition
• Collaborate with Engineering, Product, and Design teams
• Contribute to technical decisions, standards, and development best practices
• Identify, prioritize, and resolve bugs and technical debt
• Ensure the quality, stability, and scalability of solutions
• Share knowledge and contribute to the Backend Chapter
• Support the technical development of other team members (especially at Mid and Senior levels)
• Participate in hiring processes, supporting technical interviews (for more senior levels)

Backend Developer

Analytics Engineer

• Data modeling (facts, dimensions, metrics) and maintenance of pipelines/transformations using SQL and the team’s tools (e.g., dbt, Spark, or Databricks).
• Contribute to quality tests and the documentation of metrics and business rules.
• Assist in delivering tables/views for analytical consumption, ensuring best practices (naming, descriptions, consistency).
• Work alongside Data Engineering, BI/Analysts, and Data Science (on well-defined tasks).
• Participate in governance initiatives (lineage, catalog, access) and in gradual improvements to data reliability.

Data Scientist

• Desenvolver e evoluir modelos de predição para o Zé Delivery.
• Criar e manter pipelines de dados e features em PySpark para suportar modelos em escala.
• Desenvolver estratégias de recomendação de produtos e ofertas ao longo da jornada do consumidor.
• Definir, executar e analisar testes A/B para avaliação de impacto de modelos e campanhas.

Cientista de Dados

• Someone who takes personal responsibility for the squad's results and does not accept 'that's not my problem'.
• Technical Proficiency (Hard Skills):
• Strong experience with Python/PySpark.
• Experience with cloud platforms (AWS or Azure).
• Proficiency in recommendation algorithms (Collaborative Filtering, Content-based, Reinforcement Learning for personalization).
• Ability to work with real-time models and large volumes of data.
• Model validation metrics.
• Knowledge of machine learning, statistics, and predictive modeling.
• Business understanding, with a focus on impact and data-driven decision making.
• Simplicity and Scalability: Focus on building solutions that are simple to maintain and easy to scale across the company.
• Long-Term Vision: Someone who will not take ethical or technical shortcuts that create unmanageable debt in the future.
• Nice to Have:
• Experience with large-scale experimentation and A/B testing.
• Cross-functional collaboration: Prior experience partnering with Machine Learning Engineers (MLE) to deploy models.
• Familiarity with Multi-armed Bandits.
• Data Storytelling: Ability to translate complex technical metrics into business insights for Brand and Product stakeholders.
• Cost Awareness: Mindset for optimizing cloud processing costs (managing resources with discipline).