iFood, Latin America’s largest food delivery platform, is redefining how it uses data to drive innovation and efficiency with the help of Databricks, a data and AI company. The company adopted Databricks’ data intelligence platform and its DLT framework, which builds and tests reliable data pipelines, to modernize its data architecture.
The effort 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 error-free, delivering reliable performance even under the heaviest workloads,” said Thiago Julião, iFood’s data architecture specialist. “The shift from frequent errors to nearly zero issues with the migration to DLT 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—over 55 million users, 350 thousand partner restaurants, and 300 thousand active delivery drivers—the platform processes about 10 billion real-time data events daily, originating from its applications, logistics systems, and partner platforms.
“Databricks completely transformed our data operations. With DLT, we drastically reduced errors and shifted our team’s focus to strategic initiatives instead of 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 by reducing costs and increasing efficiency. With the data generated and modernization through 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 for business areas. This enables real-time analysis, A/B testing, and data-driven decisions that directly impact consumer experience and operational efficiency.
“The 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 company,” says Maristela Albuquerque, iFood’s Data Manager.
Next steps: security, scalability, and continuous innovation
With a solid technological foundation, iFood plans to expand the platform’s use with features like Databricks Asset Bundles (DABs), serverless, and sensitive column masking, further enhancing data governance and security.
“This transformation 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.