Mid-Level Data Engineer

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AB InBev

WebsiteLinkedInAll Job Openings

10,000+ employees

👥 B2C

🛍️ 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.

📋 Description

• Support the development and maintenance of data pipelines, ingestion processes, and data transformations. • Create and maintain SQL queries, Python scripts, and Spark-based workloads used for data processing and analytics. • Assist in troubleshooting pipeline failures, data quality issues, and operational incidents. • Work with senior engineers to implement schema mappings, transformation logic, and data validation rules. • Ensure datasets meet expected schemas, data contracts, and quality standards. • Support metadata management, dataset documentation, and lineage activities. • Assist in maintaining data classification information according to company standards. • Help automate repetitive operational and data management tasks to improve efficiency and reliability. • Contribute to monitoring, alerting, and operational support for data pipelines and workflows. • Participate in testing activities, including unit tests, transformation validation, and data quality checks. • Follow established engineering standards, coding practices, and team development patterns. • Learn and apply security, privacy, and compliance requirements when handling sensitive or regulated data. • Collaborate with Data Governance, Security, and Compliance teams when required. • Contribute to continuous improvement initiatives focused on data trust, reliability, and operational excellence.

🎯 Requirements

• Bachelor's degree in Computer Science, Computer Engineering, Information Systems, Data Science, Software Engineering, or related fields. • Basic to intermediate English. • Up to 2 years of experience in Data Engineering, Software Engineering, Data Analytics, or related areas. • Knowledge of SQL and Python. • Understanding of ETL/ELT concepts and data transformation processes. • Familiarity with relational databases and data warehousing concepts. • Basic knowledge of Spark, Databricks, or distributed data processing frameworks. • Familiarity with Git and version control workflows. • Basic understanding of cloud platforms such as AWS, Azure, or Google Cloud. • Knowledge of automation concepts and scripting for operational efficiency. • Basic understanding of data quality concepts and validation practices. • Familiarity with data governance principles, including metadata, ownership, stewardship, and documentation. • Basic knowledge of data classification concepts (Public, Internal, Confidential, Restricted). • Understanding of data lineage and traceability concepts. • Awareness of security best practices, including access management, secrets management, and least-privilege principles. • Strong analytical, problem-solving, and communication skills. • Willingness to learn new technologies and collaborate across teams.

🏖️ Benefits

• Health insurance • Paid time off • Professional development • Home office setup