The role involves building, maintaining, and optimizing scalable data solutions to support analytics initiatives. The focus is on ensuring code maintainability, creating reusable components, and managing reliable data pipelines. Responsibilities include refactoring legacy codebases to simplify maintenance and reduce duplication across various use cases. The position requires developing automated pipelines and designing scalable data models to support reporting needs. Collaboration with cross-functional teams is essential to improve data architecture and overall data quality.

The role requires at least five years of experience in data engineering or a similar capacity. Candidates must possess strong proficiency in GitHub version control, Databricks pipeline development, and legacy code refactoring. A solid understanding of data modeling and the design of reusable components is necessary for success. Additionally, excellent written and verbal English communication skills are required to interact effectively within the team.