• Develop and evolve data pipelines in Azure, GCP and Databricks environments, ensuring efficiency, performance and reliability; • Design solutions for large-scale data ingestion, transformation and provisioning; • Integrate data from multiple sources and systems, including Firebase; • Use Terraform for provisioning and standardizing infrastructure as code; • Identify opportunities to improve data architecture, proposing scalable and sustainable solutions; • Proactively troubleshoot issues and maintain platform stability; • Participate in technical definitions, contributing best practices and knowledge sharing; • Collaborate with multidisciplinary teams to ensure technical and business alignment; • Support initiatives to modernize and consolidate data in cloud environments.

• Desenvolver e manter pipelines de dados utilizando AWS Glue e MWAA (Apache Airflow); • Gerenciar catálogo de dados e metadados com AWS Glue Data Catalog; • Realizar consultas e transformações analíticas no Amazon Athena; • Criar e manter dashboards e relatórios no Tableau; • Atuar em squads ágeis, participando de cerimônias Scrum e entregas contínuas.

• Maintain and manage website scraping configurations using Python. • Monitor scraping configurations for errors and potential crashes. • Oversee retrieved data to detect potential issues and blockages. • Coordinate with stakeholders to understand scraping task requirements and report issues. • Prepare and share periodic reports on scraping activities with stakeholders. • Develop necessary pipelines to ingest data into the Datalake and perform required transformations.

• Technical leadership and guidance of a team of infrastructure and data engineers • Strategic development and refinement of a forward-looking Data Mesh architecture • Managing data platform scaling and ensuring structural integrity within the cloud ecosystem • Close collaboration with cross-functional teams to support data migrations toward a modern Lakehouse environment