Quality Assurance Test Lead

We are looking for a proactive Test Lead (QA), with strong technical background in Data Engineering and experience with Databricks, to lead the quality and reliability strategy in data environments. Your role will be fundamental to ensure the accuracy, integrity, and governance of modeled data, as well as to validate the results generated by analytical and conversational interfaces within the Databricks ecosystem.

Work model: Remote.

Responsibilities:

• Define and execute the data testing strategy, including Data Quality, Regression Testing, Schema Validation, Modeling Accuracy, and Referential Integrity;
• Create and automate testing and validation routines directly in the Databricks environment using SQL, Python/PySpark;
• Validate the assertiveness and consistency of responses in conversational data interfaces (Databricks Genie), ensuring alignment with the semantic layer;
• Work in direct collaboration with data architects and engineers to identify and correct inconsistencies in modeling;
• Propose and implement data quality and observability frameworks autonomously.

Requirements:

• Proven experience working as QA Lead / Test Lead in Data and Analytics projects;
• Solid background in Data Engineering, with the ability to manipulate, query, and validate large volumes of data;
• Mastery of advanced SQL and practical experience with the Databricks platform and Python/PySpark language;
• Practical knowledge of Data Quality concepts, governance, and data model validation;
• Fluent English for daily interaction with global teams;
• Proactivity, strong sense of ownership, and rigor in the quality of deliverables.