Build, maintain, and optimize scalable data solutions to support initiatives, focusing on code maintainability, reusable components, and reliable data pipelines. This role is responsible for maintaining and refactoring existing codebases, developing modular components, and ensuring high-quality, performant datasets for analytics and reporting use cases. The ideal candidate has strong experience working with code repositories, building data pipelines in Databricks or Snowflake, and designing scalable data models to support evolving analytics needs in cross-functional environments. Responsibilities Maintain, optimize, and automate existing code repositories in GitHub. Refactor legacy code to simplify maintenance, updates, and reuse across multiple use cases. Design and build modular, reusable code components to support multiple journeys and reduce duplication. Develop and manage automated data pipelines in Databricks to support datasets and downstream reporting. Consolidate key KPIs, metrics, and attributes into standardized data structures to enable flexible journey views. Build and maintain scalable data models to support current and future journey analytics use cases. Ensure data quality, performance, and reliability across data pipelines and analytics datasets. Collaborate with analytics and engineering teams to improve data processes and architecture.