• Design, build, and maintain data pipelines and lakehouse architecture • Develop and maintain SQL-based and PySpark transformations • Own data ingestion across enterprise sources • Partner with analysts and stakeholders to translate requirements • Develop Tableau data sources and enabling self-service analytics • Implement data quality practices and monitor pipelines • Establish standards for data modeling and pipeline architecture • Support AI workflows by providing curated data access • Manage platform configuration, cost, and performance • Troubleshoot data issues and resolve root causes

• Monitorar de forma contínua os pipelines de dados (batch e on-demand) • Atuar em falhas operacionais e incidentes críticos • Realizar análise de logs e troubleshooting em Dataproc, pipelines e DAGs • Acompanhar cargas, reprocessamentos e validações de dados • Manter interface com os times de Engenharia, Arquitetura, Governança e Negócio • Apoiar a estabilização dos ambientes e a melhoria contínua • Documentar incidentes, causas raiz e planos de ação

• Manage workspaces, clusters, jobs, security configurations, libraries, and overall platform health. • Build and optimize data pipelines and transformations using PySpark and T‑SQL . • Create automation and tooling using Python , Bash , and PowerShell . • Implement and automate data governance, access controls, auditability, and compliance best practices. • Translate conversational ideas into clear solution architectures; break work into tasks in Planner or Azure DevOps for team execution. • Estimate level of effort and forecast delivery dates with reasonable accuracy. • Produce high-quality documentation including workflows, gap analyses, design specs, build docs, test plans, and transition documentation. • Oversee unit, scenario-based, integrated, capacity, and parallel testing. • Participate in a 24×7×365 on-call rotation to support Databricks , SQL Server , and other relevant applications supported by the team. • Support system upgrades, patches, performance tuning, observability, and proactive monitoring. • Maintain accountability for data integrity across applications and pipelines. • Complete system build and documentation in adherence to departmental guidelines and change management policy. • Review teammates’ work and provide constructive feedback. • Communicate effectively with peers, stakeholders, and leadership; provide regular status updates and escalate issues appropriately. • Drive discussions, mentor accountable leaders, and coordinate resources across initiatives. • Provide feedback on training materials; conduct training sessions; develop and mentor other team member.

• Support and maintain data platforms, ensuring operational continuity and incident resolution. • Support workloads on Azure Databricks (notebooks, jobs, clusters, Delta tables, Unity Catalog). • Maintain and evolve CI/CD pipelines using Azure DevOps. • Troubleshoot pipelines in Azure Data Factory. • Support Power BI environments (workspaces, refresh, access management, and report availability). • Manage and maintain data structures in Azure Data Lake Storage Gen2. • Support Infrastructure as Code practices (Terraform/Azure Blueprints). • Provide operational support for Azure virtual machines. • Troubleshoot Azure networking (VNets, NSGs, DNS, connectivity). • Contribute to technical documentation, runbooks, and the knowledge base. • Participate in continuous improvement, automation, and platform standardization initiatives.