Data Engineer

Why SuperApp?YUM! SuperApp is a best-in-class application that optimizes restaurant operations and creates the best jobs.We are proud to be part of Yum! Brands & Digital Technology, a company with over 55,000 restaurants across more than 150 countries and territories, under its leading worldwide restaurant brands – KFC, Pizza Hut, Taco Bell, and The Habit Burger Grill.SuperApp is an all-in-one mobile platform specifically designed for streamlined restaurant operations. It's packed with a range of tools tailored to the needs of restaurant managers and staff, enabling them to efficiently manage daily tasks, benefit from data-driven suggestions, get timely operational prompts, and stay updated with an interactive activity feed.The innovative edge of the SuperApp lies in its 'brain layer'—an advanced recommendation engine that compiles data through different operational data sources. This engine employs machine learning to offer smart insights, thereby enhancing the decision-making process and restaurant operations.Our team operates globally with offices in the UK, Dubai, and US, as we are now installed in over 14,000 stores worldwide. The Job Data Pipeline Development: Design, build, and optimize scalable data pipelines to move and transform data efficiently. Data Integration: Use Informatica to develop ETL workflows, ensuring high-quality, error-free integration from multiple data sources into Snowflake. Data Warehousing: Leverage Snowflake to create and maintain efficient data warehouse structures, including designing and optimizing data models and managing data storage. Data Transformation: Develop scripts and leverage Informatica’s tools for data cleansing, transformation, and loading to support data analytics and reporting. Data Quality Assurance: Monitor data pipelines and resolve data quality issues by identifying discrepancies, ensuring the accuracy and reliability of data. Performance Tuning: Optimize data flows, queries, and Snowflake configurations to improve performance, reduce costs, and enhance scalability. Collaboration: Work closely with team members, and business stakeholders to understand data requirements and deliver solutions that support their needs. Documentation: Maintain clear, accurate documentation of data models, data flows, ETL processes, and troubleshooting steps. Sharing knowledge and experience with other departments/teams. Working time: 40 hours/week