October 2025: Delivered critical public health data improvements across two repositories, strengthening data access controls, expanding event and vaccination data capabilities, and enabling Google Sheets-based CDI ingestion. Also completed a targeted cleanup of protocol scaffolding to reduce technical debt. These changes delivered improved data reliability, governance, and automation for public health analytics, with demonstrations of data modelling, access-control design, and pipeline integration.

September 2025 monthly summary for prefeitura-rio/queries-rj-sms: Delivered core data-model enhancements for IplanRio integration and WhatsApp provisioning, strengthenedFicha A data quality, and expanded PIC protocol event tracking. The work enabled more reliable patient data, streamlined data sourcing with dbt ref, and improved operational readiness for WhatsApp-based communications and analytics.

August 2025 focused on expanding API coverage, stabilizing data contracts, and refining the data pipeline for prefeitura-rio/queries-rj-sms. Delivered multiple new health-condition models for the Vitacare API, implemented initial and evolved phone validation for WhatsApp IplanRio, and completed a set of quality and reliability improvements across data models, schemas, and configurations. Result: richer health data capture, improved data quality, and a more scalable, maintainable codebase with standardized naming and schemas, reducing future maintenance and enabling faster onboarding for downstream teams.

July 2025 – Prefeitura Rio / Queries RJ-SMS: Delivered core data-model and API improvements with measurable business value. Key accomplishments include introducing the APS indicators model with incremental materialization to capture historical execution data; restructuring Ficha A models to support continuidade and histórico representations; adding Prontuario Vitacare API models (derived from atendimento contínuo) and wiring them into dbt_project.yml to broaden API-derived analytics; fixing data_partition handling for atendimento_continuo (datetime casting and fim_atendimento alignment) and centralizing partition filters via bruto_atendimento CTE across related models; implementing comprehensive string/date casting across models for data type consistency. These changes improve data reliability, enable historical analytics, broaden API coverage, and improve ETL performance.

June 2025: Implemented a privacy-focused anonymized dataset for the cie dashboard, enabling daily processing of ficha_a data in prefeitura-rio/queries-rj-sms. Delivered a privacy-preserving data model and the SQL logic for the new table within the cie dashboard context, plus automated daily processing via a new project configuration tag. These changes reduce data risk, accelerate time-to-insight, and support safer, near-real-time dashboards for stakeholders.