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 run error-free, providing reliable performance even under the heaviest workloads," said Thiago Julião, data architecture specialist at iFood. The shift from frequent errors to near-zero issues with the migration to DLT not only improved operational efficiency but also freed our team to focus on strategic initiatives instead of just firefighting.
With a robust ecosystem — over 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 from operational issues to strategic initiatives," 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 hindered scaling. The migration to the platform consolidated thousands of tables into just 100, optimizing governance and improving data quality.
"Our solutions are designed to drive the growth of our clients' businesses, 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 the consumer experience and operational efficiency.
"Performance gains in the user journey have been a game-changer. Now we have greater control, speed, and reliability in how data is used across 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 platform's use with features such as 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.
