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AB InBev

Mid-Level Data Engineer

AB InBev

Data Engineer supporting development and maintenance of data pipelines for AB InBev. Collaborating with senior engineers to optimize data processing and analytics.

Posted 7/1/2026full-timeRemote • 🇧🇷 BrazilJuniorMid-LevelWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in SQL and Python for data processing and analytics, with a solid understanding of ETL/ELT concepts and data transformation processes. Capable of ensuring data quality and compliance while collaborating with cross-functional teams to enhance operational efficiency.

Highest-signal resume keywords
SQLPythonETL/ELT ConceptsData QualityData Governance

ATS Keywords

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Hard Skills
Data EngineeringData AnalyticsData TransformationData ValidationData ClassificationData LineageAutomation ScriptingRelational DatabasesSparkCloud Platforms
Soft Skills
Analytical SkillsProblem-SolvingCommunication SkillsCollaboration
Tools & Technologies
DatabricksGitAWSAzureGoogle Cloud
Industry Keywords
Data PipelinesMetadata ManagementOperational SupportSecurity Best PracticesCompliance Requirements

Tech Stack

Tools & technologies
AWSAzureCloudETLPythonSparkSQL

About the role

Key responsibilities & impact
  • 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

What you’ll need
  • 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

Comp & perks
  • Health insurance
  • Paid time off
  • Professional development
  • Home office setup