Support the development and maintenance of data pipelines (ETL/ELT) under the supervision of more experienced engineers;
Assist in structuring and preparing data in analytical environments (Data Lake and Lakehouse);
Help create and maintain databases, tables, and views, becoming familiar with data modeling patterns (star schema, snowflake);
Contribute to data ingestion, transformation and cleansing routines;
Collaborate with other data team members and business areas to facilitate access to and availability of information;
Follow the security, privacy, and compliance guidelines and best practices (including LGPD) defined by the team;
Support documentation of processes, pipelines and data dictionaries;
Use version control (Git) in daily deliveries;
Actively participate in agile ceremonies (Scrum), contributing to sprint deliverables with commitment and on schedule.

Bachelor's degree completed or in the final year in Information Technology, Computer Science, Engineering, Statistics, or related fields;
Good knowledge of SQL for querying, manipulating and transforming data;
Programming skills applied to data (Python is essential; Scala or R are a plus);
Familiarity with data modeling concepts;
Theoretical knowledge or academic/internship experience in building data pipelines;
Basic understanding of cloud data platforms and distributed processing environments;
Basic knowledge of version control (Git).
Desired:
Basic knowledge or extracurricular courses on platforms such as Databricks, MS Fabric or Azure;
Familiarity with orchestration tools (such as Azure Data Factory or Airflow);
Understanding of modern data architecture (Data Lakehouse, Delta Lake);
Basic knowledge of visualization tools (such as Power BI) for data validation;
Familiarity with deployment automation (CI/CD).

Data Engineer – Junior

Key skills