Assist with organizing, cleaning, and standardizing datasets from multiple sources, ensuring data quality, consistency, and reliability for analyses and internal processes;
Support the development and continuous improvement of data pipelines using Airflow and AWS services, contributing to automation and efficiency of data ingestion, transformation, and delivery flows;
Support maintenance and evolution of existing DAGs, ensuring adherence to development best practices, versioning, and code organization;
Monitor DAG execution, helping to identify, analyze, and resolve failures with team support to ensure stability and reliability of processes;
Work closely with data engineers, the Product Owner, and data scientists, actively participating in projects and taking on increasing complexity as technical skills develop;
Contribute to technical and conceptual documentation of processes, standards, and best practices in the data area, supporting knowledge organization and solution scalability.

Currently enrolled in a bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field;
Familiarity with SQL for querying relational databases (PostgreSQL, Firebird);
Familiarity with a programming language, preferably Python;
Basic knowledge of ETL/ELT concepts and data processing/transformation;
Familiarity with Git and version control;
Familiarity with data orchestration tools, preferably Apache Airflow;
Familiarity with cloud computing, with a focus on AWS;
Introductory knowledge of the medallion architecture (Bronze, Silver, Gold).

Life insurance
Day off during your birthday month + a credit on a Flash card as a gift to use however you like
Totalpass: For you and your dependents to take care of physical and mental health
We offer a career development plan!

Data Engineering Intern

Key skills