Rodrigo Ribeiro Gonçalves

Impact: Participated in Agile ceremonies (daily scrums, sprint planning, retrospectives) while supporting data platform modernization by transitioning legacy SSIS ETL packages to scalable Airflow and Python pipelines. Contributed to advanced analytics initiatives including Text-to-SQL and text mining projects. Action: Led data architecture and pipeline orchestration decisions, designing and optimizing ETL/ELT workflows using SQL Server, Python, SSIS, and Apache Airflow. Migrated legacy SSIS workloads to Airflow and implemented CI/CD versioning and automation using GitLab. Result: Improved performance and reliability of critical data pipelines and reduced TCO by replacing licensed SSIS solutions with Airflow and Python frameworks. Enhanced supply chain analytics through improved data availability, KPI accuracy, and reporting efficiency.

Impact: Contributed to the development and evolution of the company’s data ecosystem, supporting scalable analytics and data-driven initiatives. Action: Designed, implemented, and maintained Data Warehouse and Lakehouse pipelines using SQL Server, SSIS, and Python, with strong collaboration and integration alongside Machine Learning teams. Result: Reduced data ingestion time by 25% by redesigning ETL workflows using automation and data engineering best practices, improving efficiency and pipeline reliability.

Impact: Contributed to international data and analytics projects across the USA, Europe, and Brazil, delivering scalable and business-focused analytics solutions. Action: Developed data pipelines and analytical reporting solutions using SQL Server, Azure Synapse, Power BI, SSIS, and Python, including proof-of-concept implementations with Azure Data Factory to support modern data integration approaches. Result: Enhanced business user experience through higher-performing dashboards and reduced data load times by up to 50%. Refactored Power BI reports into Reporting Services, achieving licensing cost reductions exceeding 180%.

Impact: Established and structured the company’s financial data domain, enabling scalable and governed analytics for finance operations. Action: Designed and implemented a Snowflake-based Data Lakehouse, automated ETL pipelines using Azure Data Factory, and managed code versioning and CI/CD through Azure DevOps. Azure Keyvaults for sensitive credentials keeping. Result: Delivered more than 30 fully traceable financial KPIs, reducing reliance on manual reporting by 70% and improving data reliability for business decision-making.

Impact: Automated and structured credit portfolio monitoring for the fintech, enabling data-driven decision-making in collections and risk management. Action: Designed an Operational Data Store (ODS) using MySQL on Amazon RDS, developed ETL pipelines with Pentaho and created analytical dashboards and reports using Amazon QuickSight and Excel. Result: Delivered collection performance indicators that increased dunning process efficiency and contributed to improved delinquency management and credit portfolio performance.

Impact: Supported data-driven lead classification and sales analytics by contributing to the structuring of a centralized operational data environment within an Agile framework. Action: Designed and implemented an Operational Data Store (ODS) using Microsoft SQL Server, developed ETL processes with SSIS, and created analytical reports and dashboards using SQL Server Reporting Services (SSRS) and Power BI. Actively participated in Scrum ceremonies and Agile practices to ensure continuous delivery and collaboration. Result: Enabled more reliable and timely lead classification reporting, improving data availability and supporting better decision-making for sales and business teams.

Impact: Supported data initiatives for public sector organizations, including State Public Prosecutor’s Offices, enabling improved access to operational and analytical information. Action: Developed system integrations using Delphi and implemented ETL processes with Pentaho, working with SQL Server and Oracle databases to consolidate and prepare data for reporting. Result: Reduced report processing time by 40% through performance tuning, process optimization, and automation, improving data delivery efficiency.

Impact: Provided support and performance improvements for databases in a multicloud environment. Action: Performed database administration and migration between AWS and Azure, along with development using SSIS and performance tuning. Result: Reduced operational costs through better cloud resource allocation and eliminated performance bottlenecks.

Impact: Integrated and optimized data from the notary management system (Cart). Action: Developed ETLs using Pentaho and optimized queries in MySQL. Result: Reduced report generation time by 60%.

Impact: Implemented Business Imtelligence solutions for SENAI and FIESC. Action: Developed cubes and reports using SQL Server, SSIS, and Reporting Services. Result: Reduced the time required to generate management dashboards by 50%.

Impact: Created the company's CRM Data Warehouse. Action: Modeled data, developed strategic KPIs, and built pipelines using SQL Server and SSIS. Result: Increased campaign effectiveness by 45% through monitoring of HOTs and TMs.