• Lead the design and implementation of data ingestion architectures in Snowflake, ensuring scalability and reliability. • Own the development of end-to-end ELT pipelines integrating multiple data sources. • Design and enforce data quality frameworks, including validation rules, testing strategies, and monitoring. • Apply and drive Medallion Architecture (Bronze, Silver, Gold) best practices across data pipelines. • Build and optimize data pipelines and architectures on AWS (S3, Glue, Lambda, EMR, etc.). • Develop and enhance data validation and ingestion frameworks, including UI components (Streamlit-based) when needed. • Act as a technical leader, guiding best practices in data engineering, governance, and pipeline reliability. • Proactively identify risks, bottlenecks, and data quality issues, and implement mitigation strategies before they impact delivery. • Contribute to data governance initiatives, including data definitions, lineage, and stewardship practices. • Drive documentation and continuous improvement of data platform processes.

• Maintain and evolve corporate data environments • Develop, maintain and optimize ETL (Extract, Transform, Load) processes • Perform database maintenance and tuning to ensure performance, availability and data integrity • Administer and support SAS environments, including tasks related to SAS DBA and SAS DI Studio (SIS) • Support legacy applications and processes, proposing continuous improvements • Monitor, analyze and address failures in data load and integration processes • Handle a significant volume of tickets, meeting established SLAs and ensuring operational continuity • Assist in identifying and resolving incidents related to the data environment • Produce and maintain technical documentation for processes and procedures • Participate in continuous improvement, automation and data architecture modernization initiatives • Support projects related to the implementation and evolution of the Data Lake

• Design and maintain enterprise reporting architecture supporting program management, operational reporting, and executive dashboards. • Develop scalable data models, reporting frameworks, and business intelligence solutions using industry best practices. • Collaborate with business stakeholders to define reporting requirements, key performance indicators (KPIs), and data visualization strategies. • Design and optimize SQL queries, stored procedures, and data pipelines supporting enterprise reporting initiatives. • Develop executive dashboards and interactive reports using Power BI, Tableau, or similar business intelligence platforms. • Ensure reporting accuracy through data validation, quality assurance, and data governance processes. • Partner with Data Analysts, Business Analysts, and technical teams to identify new reporting opportunities and improve data accessibility. • Maintain technical documentation, data dictionaries, reporting standards, and architectural diagrams. • Support executive governance meetings by providing reporting solutions and analytical insights that inform strategic decision-making. • Recommend continuous improvements to reporting architecture, data integration processes, and business intelligence capabilities.

• Lead the data dimension of the migration for the SAP SQL Anywhere layer (~3.5M rows; 8,946 triggers; 805 stored procedures; 40k+ access points) • Evaluate and deploy a change data capture mechanism to enable coexistence stitching (no managed CDC for SQL Anywhere; dbtran is not CDC) • Ensure single-writer ownership during the dual-run • Protect data integrity and performance of the fiscal ledger system • Maintain the data side of the equivalence harness (production history replay) • Produce masked/synthetic datasets in compliance with Brazil's LGPD • Define the migration and reconciliation plan in waves, avoiding split-brain • Extract and document embedded business logic as reusable artifacts