Responsible for the development and operation of the Data internal platforms at the company, managing 10's of thousands of jobs and data products and serving thousands of internal customers.Responsible for iFood's ML Platforms and Feature Store, and management of its development and operations team, serving hundreds of Data Scientists at the company.Responsible for the Generative AI initiative and team, and also Brazil's first company with access to dedicated OpenAI capacity.Also responsible for iFood's data governance in cooperation with the legal Privacy team.

iFood is a market leader in the segment of food delivery in Latin America. Our app is used by millions of people and generates terabytes of data every day.I am responsible for our Data Lake initiative (DataOps) as well as the teams developing the data pipelines on Spark (Data Architecture) and maintenance of our Big Data infrastructure (Data Platform). We provide data processing capabilities to the enterprise through our Data Lake, data microservices and Machine Learning platform (MLOps & Feature Store). We work alongside other Data, Engineering and Data Science teams inside our company to provide intelligence capabilities to our systems.Our Big Data stack is built on top of Amazon Web Services (AWS), Spark (Databricks), Tableau, Python, Scala among other technologies.We are also responsible for providing extensive training and support in our tool set for Data Analysts and Business Analysts throughout iFood, with over 3000 internal clients.In the past I was also responsible for our Data Science teams for large scale systems inside iFood, including fraud detection, recommendation systems/ranking, product classification among others.

Responsible for the company's data strategy, as well as a data governance policy applied to all start-ups (10+) within the partnership programme.Management of three main teams related to the data strategy of the company: Big Data Architecture, Data Science, Data Warehousing, Data Governance and Business Intelligence. Provide technical leadership and development of the teams' skills.Development of modern Big Data projects with cloud (Amazon Web Services) technology, including the company's Data Lake, Spark, data pipelines, and Deep Learning.Build and manage Data Analytics capabilities within the company involving Big Data and Data Warehousing technology, Machine Learning and Statistics pipelines and Data Visualizations dashboards and reports. Implementation of Agile methodologies and management of projects involving Data Science studies and data processing.

Architect and deliver data solutions for enterprises.Development of training programs for data professionals, including technology tools, best practices and overall data pipeline (management, cleansing and analysis). Build and deliver Data Warehouse/Business Intelligence (DW/BI) projects. Migration of existing data infrastructure to cloud environments.Speaker at various conferences, including Microsoft Insights powered by TechEd.

Worked in NeoGIG, a web-based GIS (Geographic Information System) designed for market analysis and decision making support.Responsible for the company's Data Warehousing initiative. Mining, integration and cleansing of data from heterogeneous sources from both inside and outside the company.Implementation and optimization of economic models in Python involving spatial and socioeconomic data, as well as querying performance. Training of the team in technology tools ranging from SQL Server to Python.

Develop, migrate, deploy and tune the pilot DB2 for z/OS subsystem on the IBM z196 Mainframe. Administration of DB2 LUW instances running on z/Linux SUSE Enterprise and SQL Server databases running on Fujitsu PRIMEQUEST high-end servers.Help capacitate all DBA teams, including SQL Server and DB2.