Direct data management projects, focusing on AI governance, data quality, and certification for off-chain data oracles in blockchain networks. Collaborate with cross-functional teams to create a unified data strategy, prioritize analysis requests based on business needs, and ensure the composition and provisioning of Data Products aligns with strategic goals. Combine leadership with hands-on development of data products, visualizations, and governance policies that support business growth.Key Achievements:Improved data accuracy by 25% through new data quality processes in AI governance projects.Increased stakeholder and product manager satisfaction by 15% via enhanced NPS.Delivered 95% of projects on time and within budget.Enhanced Data Product composition and governance, ensuring data policies were integrated and provisioned across teams for consistent use.Technological Stack: GCP (BigQuery, Spanner, Dataproc, Dataflow, Dataplex, Data Catalog, Blockchain, SQL, Python, Power BI, Informatica, GitHub, GitLab, DataOps.Frameworks/Methods: DAMA-DMBOK, COBIT, DCAM, GDPR, TOGAF, Zachman Framework, Data Mesh, Medallion Architecture, LGPD, FAIR, AI TRiSM.

Led educational modules on Data Governance, Data Architecture, Data Quality, and Metadata Management, incorporating industry best practices from the DMBOK II framework. Emphasized the application of theoretical knowledge to practical challenges in data management and governance, preparing students for real-world scenarios.Key Achievements:Rated 4.5 out of 5 by students for course effectiveness and teaching style.Bridged the gap between theoretical content and industry practice.Developed engaging teaching materials that fostered a deep understanding of complex topics.Technological Stack: SQL, Python, Power BI, Trello.Frameworks/Methods: DAMA-DMBOK, COBIT, DCAM, GDPR, TOGAF, Zachman Framework, Data Mesh, Medallion Architecture.

Directed data governance strategies, ensuring data quality, security, and compliance with LGPD and BACEN guidelines for financial products on the GCP platform. Responsible for the creation, maintenance, and development of data products across various financial sectors, including Cartões, Duplicata Escritural, Recebíveis de FIDCs, Recebíveis de Agronegócio, Recebíveis Imobiliários, Inteligência de Dados, and Seguros. Developed and applied data governance and security policies, collaborating with stakeholders to align data and AI solutions with business objectives and regulatory standards. Led the implementation of data cataloging and metadata management projects, improving data literacy and process efficiency.Key Achievements:Improved data quality by 30% and reduced operational costs by 20% through efficient data governance strategies.Achieved 100% regulatory compliance, including LGPD and BACEN guidelines.Implemented data governance and security policies that ensured compliance across all operations.Integrated 30+ data sources using ETL solutions and BigQuery, streamlining operations.Developed AI models that improved financial forecast accuracy by 15%.Led the development of data products for Cartões, Recebíveis de FIDCs, Recebíveis de Agronegócio, and more, ensuring governance policies were embedded throughout.Technological Stack: GCP (BigQuery, Spanner, Dataproc, Dataflow, Dataplex, Data Catalog), SQL, Python, Power BI, Jira, Confluence, Databricks (Delta Lake, Unity Catalog, Delta Sharing).Frameworks/Methods: DAMA-DMBOK, TOGAF, LGPD, BACEN, Medallion Architecture, Data Mesh.

Orchestrated data visualization projects using Google Cloud Looker and Apache Superset, integrating technologies and teams through a combination of soft and hard skills. Developed data extraction processes, creating a semantic layer based on business domains (Data Mesh). Applied structured methods for dashboard development, reporting, and consumption of master data APIs.Key Achievements:Increased data accessibility and accuracy by 25% through the implementation of a new data visualization process.Reduced dashboard development time by 30% by integrating multiple data sources into a unified semantic layer.Improved data-driven decision-making for stakeholders by crafting clear, actionable dashboards using Google Cloud Looker and Apache Superset.Technological Stack: Google Cloud Looker, Apache Superset, Data Mesh, SQL, Python, Google Cloud Platform, Master Data APIs.Frameworks/Methods: DAMA-DMBOK, Data Mesh, Medallion Architecture, Agile (Scrum, Kanban).

Directed the implementation of data governance and AI policies, overseeing the evolution of data products and the AWS data lake to align with organizational goals. Led data performance monitoring across corporate, agribusiness, middle market, and SME segments, ensuring data products for credit operations, receivables anticipation, fees, and investments met business needs. Collaborated with product managers to integrate data quality management, metadata governance, and policy enforcement into product development.Key Achievements:Reduced data errors by 40% through the implementation of governance policies.Increased data integration by 50% between internal systems and the AWS data lake.Boosted customer satisfaction by 25% through enhanced data products.Improved understanding of technical concepts among non-technical stakeholders by 30%.Technological Stack: AWS (S3, Redshift, Athena, IAM, Lake Formation, Macie, Glue Data Catalog), Neo4j, Power BI, QlikView.Frameworks/Methods: Data Lake, Medallion Architecture, Data Mesh, DAMA-DMBOK, TOGAF, LGPD.

Orchestrated LGPD and Data Governance projects, integrating teams and technologies to ensure compliance with Law No. 13.709 for clients in various industries. Led consultative leadership and project management efforts to align internal (Data Controller) and external (Data Operator) data treatments with legal requirements. Mentored Data Protection Officers (DPOs) at the intersection of Law, Technology, and Data, ensuring the effective implementation of data governance strategies.Key Achievements:Ensured 100% LGPD compliance for clients by establishing clear data governance processes and frameworks.Reduced legal risks by 20% through the implementation of risk management protocols in data processing.Enhanced data modeling and visualization practices, improving clients' operational efficiency by 30%.Technological Stack: SQL, Python, Power BI, Data Modeling Tools, Cloud Platforms.Frameworks/Methods: LGPD Compliance, DAMA-DMBOK, GDPR, MDM, Data Governance, Agile (Scrum, Kanban), Risk Management.

Led the digital and data services area, managing teams across Asia and the USA to implement data and AI strategies. Directed projects involving corporate data warehouses, data lakes, and IBM cloud solutions, driving operational efficiency and data-driven decision-making. Specialized in Data Engineering, Data Governance, and AI with IBM Watson products, balancing leadership with hands-on development of data products, metrics, and pre-sales support.Key Achievements:Increased operational efficiency by 35% through the implementation of an enterprise data warehouse.Reduced data access time by 40% by introducing a cloud-based data lake.Expanded B2B client portfolio by 20% through data and AI strategies for B2B markets.Delivered 90% of projects on time and within budget using agile methodologies.Improved data accuracy by 20% by implementing best practices in data governance and AI with IBM Watson.Recognized with the IBM Upgrowth Data Governance – Practice, IBM Gerstner Award for Client Excellence, and IBM GBS Service Excellence Award.Technological Stack: IBM Watson, IBM Cloud, DB2, Oracle, Teradata, IBM InfoSphere, Informatica, IBM Guardium, IBM DataStage, IBM Cognos Analytics, IBM QRadar, MicroStrategy, QlikView.Frameworks/Methods: DAMA-DMBOK, COBIT, DCAM, GDPR, TOGAF, Zachman Framework, IBM Data Governance Council Framework, FAIR, Agile (Scrum, Kanban), Data Warehouse.

Designed and implemented data architecture solutions, ensuring the full lifecycle management of data, from acquisition to transformation, storage, and delivery. Specialized in databases, content management, and business intelligence, with a focus on delivering meaningful and actionable data insights that align with regulatory requirements. Led projects involving Business Intelligence, Big Data, and Data Governance, balancing technical leadership with hands-on solution design.Key Achievements:Delivered comprehensive data architecture solutions that improved data accessibility and usability across multiple industries.Enhanced data security and compliance by implementing robust data governance frameworks.Improved operational efficiency by optimizing data processes, resulting in faster data access and decision-making.Technological Stack: IBM Watson, DB2, Oracle, Teradata, IBM InfoSphere, Informatica, IBM DataStage, IBM Cognos Analytics, QlikView.Frameworks/Methods: DAMA-DMBOK, GDPR, Data Governance, Data Warehousing, Agile (Scrum, Kanban).

Optimized data processes, leveraging cutting-edge technologies to deliver business-driven data insights. Focused on digital product design, data migration plans, and data architecture for both structured and unstructured data in Data Warehouses and Data Lakes. Applied analytical techniques to manipulate and clean large datasets, unlocking valuable insights to drive decision-making and business success.Key Achievements:Improved data processing efficiency by optimizing Data Warehouses and Data Lakes.Delivered business insights by applying data-driven methods to solve complex problems.Enhanced data accessibility and usability, driving better decision-making across multiple industries.Technological Stack: IBM Watson, DB2, Oracle, Teradata, IBM InfoSphere, Informatica, IBM DataStage, IBM Cognos Analytics, QlikView, ER-Win.Frameworks/Methods: DAMA-DMBOK, Data Governance, Agile (Scrum, Kanban), Data Warehousing.

Served as a key advisor for the DAMA Brazil chapter, focusing on promoting data management best practices and fostering a proactive approach to Data Governance. Worked closely with professionals and organizations to help them understand and implement data governance frameworks, emphasizing the importance of compliant and efficient data management strategies. Advocated for industry awareness of data-driven insights, providing guidance on aligning data policies with evolving regulatory environments.Key Responsibilities:Advised organizations on adopting data governance frameworks and best practices.Supported chapter members in understanding and implementing data-driven insights.Played a pivotal role in promoting data management awareness ahead of regulatory developments.

Led the DAMA Brazil chapter's initiatives to foster a culture of excellence in Data Governance and CDO leadership. Developed and executed tailored Data Events for the Brazilian market, establishing strong relationships with C-level executives (CxOs) from private companies and key decision-makers in public institutions. Played a pivotal role in translating the DMBOK into Portuguese and ensuring the CDMP certification exams were available during major data events, enhancing the professionalism and recognition of data management in Brazil.Key Achievements:Built a strong network of CxOs and decision-makers across private and public sectors to promote Data Governance.Organized successful Data Events, modeled after Enterprise Data World, tailored to the Brazilian market.Facilitated the translation of the DMBOK into Portuguese, making it accessible to a wider audience.Introduced CDMP certification opportunities, raising the standards of data management professionals in Brazil.

Led a BI and Analytics management program for banking services with a budget of R$ 5.4 million, developing an analytical environment that supported branch managers in selling banking services. Implemented Master Data Management (MDM) using the FS-LDM model for the financial sector, significantly improving data quality. Managed multiple projects, including the integration of 70+ data sources for the Basel II project and the creation of a Business Intelligence Competency Center (BICC) for a BPO and CRM company.Key Achievements:Reduced data quality issues by 60% through MDM implementation using the FS-LDM model.Integrated over 70 data sources into an EDW platform for the Basel II project, improving reporting accuracy.Developed a loyalty program and utilization index for financial products, increasing customer engagement.Presented at NRDM 2012 on Data Quality and Governance, showcasing best practices in data management.Technological Stack: Teradata, SQL, FS-LDM (Financial Services Logical Data Model), EDW (Enterprise Data Warehouse), MDM Tools, BI Tools.Frameworks/Methods: Data Governance, MDM, Basel II Compliance, Data Quality Management, BICC, Agile (Scrum, Kanban).

As a consultant and owner of my own firm, I excel at prospecting, qualifying, conducting initial visits with pre-sales and technical diagnosis. My strength lies in writing clear and concise commercial proposals, and I ensure transparency and objectivity in presenting solutions to clients. I work collaboratively with technical teams to define project activities, allocate resources with suitable profiles, and monitor project progress to meet commercial and technical requirements.With expertise in Business Discovery planning, Data Profiling, and Quality Data projects, I have experience in developing and implementing processes for analysis, measurement, cleansing, and improvement. I also have practical experience in implementing Data Integration techniques with its three pillars of consolidation (ETL), federation (EII), and propagation (EAI), as well as knowledge of Master Data Management (MDM) processes. My experience in conceptual, logical, and physical modeling for both EDW and derived and non-derived Data Marts, as well as my application of methodologies for Multidimensional Data Warehouse Architecture (MD) and Corporate Information Factory (CIF), further enhance my capabilities. Additionally, I possess hands-on experience in building cleansing, transformation, and loading processes for EDW and Data Marts.

Led corporate BI and EDW projects, specializing in data modeling and the implementation of Master Data Management (MDM) strategies for the finance sector. Utilized the FS-LDM logical data model to improve data quality and streamline the management of critical data elements, such as products, parts, contracts, and locations. Played a key role in the Basel II project, integrating over 70 data sources into the existing EDW platform on Teradata, ensuring accurate data reporting and compliance.Key Achievements:Reduced data quality issues by 20% through MDM implementation in analytical environments.Integrated 70+ data sources into the EDW platform for the Basel II project, improving data accuracy.Increased sales of financial products by enhancing data quality for the Client Relations department.Technological Stack: Teradata, SQL, FS-LDM (Financial Services Logical Data Model), EDW (Enterprise Data Warehouse), MDM Tools, BI Systems.Frameworks/Methods: Data Governance, MDM, Basel II Compliance, Data Quality Management, BI Development, Agile (Scrum).

At Bosch and Siemens Home Appliances (B/S/H/), a German home appliance manufacturing company, I started as a programmer and later took on the role of coordinating BI initiatives, generating analytical information for business decisions in commercial, logistics, and field service.

As an IT analyst, I was responsible for administering the LAN/WAN network for a leading financial organization. Through my expertise, I ensured smooth operations of the network and provided technical support to resolve issues in a timely manner. My strong analytical and problem-solving skills enabled me to enhance network performance and security, ensuring seamless connectivity for critical business operations.

Banking Automation: Successfully installed and maintained banking automation systems for Banco Noroeste, Sudameris, and Boa Vista. Provided training and support to ensure seamless adoption of new technology.