The iFood, the largest food delivery platform in Latin America, is redefining how it uses data to drive innovation and efficiency with the help of Databricks, a data and AI company. The company has adopted Databricks’ data intelligence platform and its DLT framework, which builds and tests reliable data pipelines, to modernize its data architecture.
The effort has led to a series of operational gains, including a 67% reduction in processing and storage costs, 70% less effort in pipeline maintenance, and a 30% reduction in code development time.
“The pipelines now run without errors, delivering reliable performance even under the heaviest workloads,” said Thiago Julião, a data architecture expert at iFood. “The shift from frequent errors to almost zero issues with the migration to DLT has not only improved operational efficiency but also freed our team to focus on strategic initiatives rather than just putting out fires.”
With a robust ecosystem – with over 55 million users, 350 thousand partner restaurants, and 300 thousand active couriers – the platform processes around 10 billion real-time data events daily, originating from its apps, logistics systems, and partner platforms.
“Databricks has completely transformed our data operations. With DLT, we have dramatically reduced errors and shifted our team’s focus to strategic initiatives rather than operational issues,” says Julião.
From a fragmented environment to a unified architecture
Before implementation, the company faced challenges with fragmented architecture and manual processes, which often led to errors and made scaling difficult. The migration to the platform consolidated thousands of tables into just 100, optimizing governance and improving data quality.
“Our solutions are designed to drive our clients’ business growth, reduce costs, and increase efficiency. With the data generated and modernization with DLT, iFood has access to strategic insights that help improve the customer experience when placing orders,” explains Marcos Grilanda, Vice President and General Manager for Latin America.
Today, with a structured and layered approach, the platform ensures data ingestion with second-level latency, automated validations, and simplified access to business areas. This allows real-time analysis, A/B testing, and data-driven decisions that directly impact consumer experience and operational efficiency.
“Performance gains in the user journey were a game-changer. We now have greater control, speed, and reliability in how data is used across the entire company,” says Maristela Albuquerque, Data Manager at iFood.
Next steps: security, scalability, and continuous innovation
With a solid technological foundation, iFood plans to expand the use of the platform with features such as Databricks Asset Bundles (DABs), serverless, and sensitive column masking, further enhancing data governance and security.
“This transformation has allowed us to eliminate inefficiencies, accelerate solution development, and, most importantly, build a solid foundation for continuous innovation,” concludes Gabriel Campos, Head of Data and AI at iFood.
