
10,000+ employees
đĽ B2C
đď¸ eCommerce
B2C ⢠eCommerce ⢠Food & Beverage
AB InBev is a global brewing company known for its extensive portfolio of over 500 beer brands, including iconic global and local names. Committed to sustainability and responsible drinking, the company has a heritage spanning more than 600 years. AB InBev continually seeks innovation in brewing and serves to celebrate beer as a beverage of moderation.
đ April 1
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10,000+ employees
đĽ B2C
đď¸ eCommerce
B2C ⢠eCommerce ⢠Food & Beverage
AB InBev is a global brewing company known for its extensive portfolio of over 500 beer brands, including iconic global and local names. Committed to sustainability and responsible drinking, the company has a heritage spanning more than 600 years. AB InBev continually seeks innovation in brewing and serves to celebrate beer as a beverage of moderation.
⢠Implement ETL/ELT solutions and data integration between multiple systems and data sources. ⢠Design, implement, and maintain data pipelines to ingest, store, and process large volumes of data. ⢠Collaborate with other teams to ensure data security and compliance. ⢠Design, develop, and implement solutions to optimize the performance and scalability of data processing systems.
⢠Bachelor's degree in Computer Science, Computer Engineering, Information Systems, Systems Analysis and Development, or similar; ⢠Intermediate English; ⢠Apply knowledge of data pipeline concepts and tools to implement data transformation, cleaning, and aggregation tasks. ⢠Use data pipeline frameworks and libraries to automate data processing tasks and optimize workflows. ⢠Follow best practices for developing data pipelines, including version control, testing, and thorough documentation. ⢠Apply programming skills in Python, PySpark, Scala, and SQL to effectively manipulate and transform data. ⢠Understand and utilize cloud computing platforms and services offered by providers such as AWS, Azure, and Google Cloud. ⢠Develop data pipelines using orchestration frameworks (e.g., Apache Airflow, Luigi, Mage, Databricks Workflows), integrating with PySpark and/or Scala as needed. ⢠Understand and apply software design principles to data engineering projects. ⢠Apply data modeling techniques to design efficient and scalable data models. ⢠Optimize PySpark and SQL query performance, considering data volume, query complexity, and system resources. ⢠Use data tools for ingestion, transformation, analysis, and visualization.
⢠Performance-based bonus* ⢠Attendance bonus* ⢠Private pension plan ⢠Meal allowance ⢠Casual office and dress code ⢠Days off* ⢠Health, dental, and life insurance ⢠Medicines discounts ⢠WellHub partnership ⢠Childcare subsides ⢠Discounts on Ambev products* ⢠Clube Ben partnership ⢠Scholarship* ⢠School materials assurance ⢠Language and training platforms ⢠Transport allowance
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