Actively participate in refinement sessions, proposing testable acceptance criteria and identifying quality risks from the earliest stages
Create and maintain comprehensive test plans
Develop and maintain automated tests for APIs and frontends, aligning automation to the product's critical flows
Perform integration testing, data validation, and end-to-end testing, focusing on real system coverage
Identify and anticipate quality issues, proactively mitigating defects and supporting platform stability
Collaborate with developers, Product Owners, and other stakeholders to ensure continuous quality throughout the software lifecycle
Continuously evaluate QA tools, methods, and metrics, proposing improvements aligned with industry best practices
Support the structuring of the QA area within the squad, helping to define processes, best practices, and quality standards
Serve as a technical reference for less-experienced profiles, contributing to team growth and a quality-first culture
Contribute to the definition and implementation of testing strategies in distributed environments, ensuring reliability, traceability, and reproducibility of deliveries.

Practical experience with Python
Strong knowledge of a programming language: syntax, control structures, etc.
Practical knowledge of data management and workflow platforms
Practical experience with ETL tools (such as Pentaho, Databricks, and Airflow) for monitoring and validation, and testing large-volume data flows and complex pipelines
Data Quality: solid understanding of data quality principles and validation methodologies
Hands-on experience in the ETL process (extraction, transformation and loading)
Practical knowledge of Great Expectations
Fundamentals of compliance and data privacy (LGPD, GDPR)
Deep understanding of testing methodologies (black-box, white-box, regression, etc.)
Deep knowledge of test types (integration, functional, acceptance tests, etc.)
Strong knowledge of testing techniques such as Equivalence Partitioning and Boundary Value Analysis
Git and Gitflow: versioning, branches, merge, merge request
Strong knowledge of SQL/NoSQL databases
Solid understanding of Agile methodologies and practical experience with Scrum or Kanban

Mid-level QA Engineer

Key skills