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 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 operate flawlessly, delivering reliable performance even under the heaviest workloads,” said Thiago Julião, data architecture specialist at iFood. “The shift from frequent errors to near-zero problems with the migration to DLT not only improved operational efficiency but also freed up our team to focus on strategic initiatives instead of just putting out fires.”
With a robust ecosystem — more than 55 million users, 350,000 partner restaurants, and 300,000 active delivery drivers — the platform processes approximately 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 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 frequently led to errors and hindered scalability. Migrating to the platform consolidated thousands of tables into just 100, optimizing governance and improving data quality.
“Our solutions are designed to drive business growth for our clients by reducing costs and increasing efficiency. With the data generated and modernization through DLT, iFood has access to strategic insights that contribute to improving 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 analytics, A/B testing, and data-driven decisions that directly impact customer experience and operational efficiency.
“The performance gains in the user journey were a game-changer. Now we have greater control, speed, and reliability in how data is used throughout the 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 operation, and masking of sensitive columns, further enhancing data governance and security.
“This transformation has allowed us to eliminate inefficiencies, accelerate the development of solutions and, above all, build a solid foundation for continuous innovation,” concludes Gabriel Campos, Head of Data and AI at iFood.
