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Intermediate Data Engineer

3 weeks, 1 day ago
Brazil
Junior
Data Engineer
Software Development
Apache Spark AWS Azure CI/CD Databricks dbt GCP Git GitHub Actions JSON Python Secrets Management SQL
Apply Now
AB InBev

AB InBev

AB InBev is the world's largest brewer, committed to bringing people together for a better world. With a diverse portfolio of over 500 beer brands, including global favorites like Budweiser, Corona, and Stella Artois, the company focuses on brewing the...

Beverages
100K+
Founded 2008
View All Jobs 7

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 for data processing and analytics.
  • Troubleshoot 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, lineage activities, and data classification efforts.
  • 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.
  • Collaborate with Data Governance, Security, and Compliance teams and contribute to continuous improvement initiatives.

Requirements

  • Bachelor's degree in Computer Science, Computer Engineering, Information Systems, Data Science, Software Engineering, or a related field.
  • Basic to intermediate English proficiency.
  • Up to 2 years of experience in Data Engineering, Software Engineering, Data Analytics, or a related area.
  • 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 such as Public, Internal, Confidential, and 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.
  • Experience with Databricks, dbt, or similar technologies is preferred.
  • Familiarity with CI/CD tools such as GitHub Actions or Azure DevOps is preferred.
  • Familiarity with APIs, JSON, event-driven architectures, or messaging systems is preferred.
  • Exposure to vulnerability scanning, secret scanning, or secure development practices is preferred.
  • Understanding of privacy regulations such as LGPD, GDPR, or similar frameworks is preferred.

Interested in this position?

Apply directly on the company website

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