
Over a two-month period, contributed to the prefeitura-rio/queries-rj-iplanrio and prefeitura-rio/prefect_rj_iplanrio repositories by developing and enhancing data models, focusing on geographic enrichment, payroll calculations, and schema normalization. Leveraged SQL and YAML to implement robust ETL improvements, introduce new fields for address and payroll data, and align data types for cross-model compatibility. Applied advanced data validation, deduplication strategies, and test-driven development to ensure data integrity and reporting accuracy. Streamlined YAML configurations and validation logic, improving maintainability and reliability. Demonstrated strengths in data transformation, database management, and pipeline development, laying groundwork for scalable analytics and future feature expansion.
March 2026 monthly summary for prefeitura-rio/queries-rj-iplanrio focused on delivering data quality improvements, schema normalization, and payroll model enhancements that significantly improve reporting accuracy and maintainability.
March 2026 monthly summary for prefeitura-rio/queries-rj-iplanrio focused on delivering data quality improvements, schema normalization, and payroll model enhancements that significantly improve reporting accuracy and maintainability.
February 2026: Delivered core data-model enhancements, robust geographic data enrichment, and cross-model alignment to improve data capture, integrity, and analytics readiness across prefeitura-rio/prefect_rj_iplanrio and prefeitura-rio/queries-rj-iplanrio. Key efforts included adding the endereco field to the Processo table, introducing uf_codigo_ibge with ETL improvements and more resilient joins, hardening data integrity for id_categoria with tests and metadata updates, and aligning contrato_id types to ensure cross-model compatibility. These changes boost data completeness, reliability of joins, and consistency across datasets, enabling more accurate reporting and business insights. Demonstrated proficiency across SQL modeling, dbt testing, datetime parsing, validation, and YAML/schema alignment.
February 2026: Delivered core data-model enhancements, robust geographic data enrichment, and cross-model alignment to improve data capture, integrity, and analytics readiness across prefeitura-rio/prefect_rj_iplanrio and prefeitura-rio/queries-rj-iplanrio. Key efforts included adding the endereco field to the Processo table, introducing uf_codigo_ibge with ETL improvements and more resilient joins, hardening data integrity for id_categoria with tests and metadata updates, and aligning contrato_id types to ensure cross-model compatibility. These changes boost data completeness, reliability of joins, and consistency across datasets, enabling more accurate reporting and business insights. Demonstrated proficiency across SQL modeling, dbt testing, datetime parsing, validation, and YAML/schema alignment.

Overview of all repositories you've contributed to across your timeline