The role involves designing and implementing a data quality framework across various data layers. The engineer will build and maintain automated quality checks within data pipelines to ensure data reliability and consistency. Responsibilities include performing reconciliation between source systems and data layers while validating identity resolution outputs. The position requires conducting end-to-end pipeline testing and partnering with engineering teams to define acceptance criteria for deliverables. Additionally, the role entails documenting quality assurance processes and monitoring pipeline health to resolve data quality incidents.

Candidates must possess at least three years of experience in data engineering or data quality roles. Required technical proficiencies include working with Azure-based data platforms, Databricks, and SQL. Applicants should have a strong understanding of data quality frameworks, testing methodologies, and layered architectures. Advanced English proficiency is necessary for communication with global teams.