
Luciano Muniz developed and enhanced municipal data platforms for the prefeitura-rio/queries-rj-iplanrio and prefeitura-rio/queries-rj-sms repositories, focusing on data modeling, ingestion, and consolidation for domains such as active debt, mental health, and infrastructure. He designed robust ETL pipelines and database schemas using SQL, YAML, and dbt, enabling scalable ingestion and reporting for large datasets. Luciano standardized data naming, integrated new payment and contributor data sources, and improved reporting accuracy by consolidating taxpayer and payment information. His work demonstrated depth in data warehousing, schema management, and analytics readiness, consistently delivering maintainable, well-documented solutions aligned with project governance.
November 2025 performance focused on delivering a consolidated debt and payment data platform for the prefeitura-rio project. Delivered three major features enhancing data modeling, consolidation, and payment integration: 1) Active debt payment guides data model and reporting improvements; 2) Taxpayer debt and payment guides data consolidation and reporting; 3) Payment processing enhancements and advanced debt data querying. These efforts consolidated data by contributor/ taxpayer, introduced reporting-ready structures, and added support for barcode, Pix ID, and QR code payments. Result: a single source of truth for active debt, improved reporting accuracy and timeliness, and enhanced payment experience. Tech stack/skills demonstrated included SQL data modeling (raw and mart schemas), ETL consolidation, unnest operations, complex joins/aggregations, reporting optimization, and contributor-level data consolidation; collaboration across teams, and alignment with homologation activities.
November 2025 performance focused on delivering a consolidated debt and payment data platform for the prefeitura-rio project. Delivered three major features enhancing data modeling, consolidation, and payment integration: 1) Active debt payment guides data model and reporting improvements; 2) Taxpayer debt and payment guides data consolidation and reporting; 3) Payment processing enhancements and advanced debt data querying. These efforts consolidated data by contributor/ taxpayer, introduced reporting-ready structures, and added support for barcode, Pix ID, and QR code payments. Result: a single source of truth for active debt, improved reporting accuracy and timeliness, and enhanced payment experience. Tech stack/skills demonstrated included SQL data modeling (raw and mart schemas), ETL consolidation, unnest operations, complex joins/aggregations, reporting optimization, and contributor-level data consolidation; collaboration across teams, and alignment with homologation activities.
2025-10 monthly summary: Delivered core data platform improvements across two repos to strengthen financial analytics for municipal debt. Focused on DAM data model overhaul with ETL enhancements, dbt_utils upgrade, and scalable large-table data pipelines. Result: higher data quality, governance, and readiness for scalable reporting.
2025-10 monthly summary: Delivered core data platform improvements across two repos to strengthen financial analytics for municipal debt. Focused on DAM data model overhaul with ETL enhancements, dbt_utils upgrade, and scalable large-table data pipelines. Result: higher data quality, governance, and readiness for scalable reporting.
September 2025 focused on establishing a robust data foundation for the Municipal Active Debt (DAM) domain in prefeitura-rio/queries-rj-iplanrio. Delivered foundational data models covering active debt records, person entities, CDA (Certidões de Dívida Ativa), payment guides and quotas, and associations with properties and related financial data. Performed a targeted data model refactor to simplify the structure by removing an optional linkage and consolidating related representations, preparing the DAM module for data loading and analysis. The work sets the stage for downstream analytics, reporting, and integration with existing systems. No customer-reported defects; all work completed with quality and in alignment with architectural guidelines.
September 2025 focused on establishing a robust data foundation for the Municipal Active Debt (DAM) domain in prefeitura-rio/queries-rj-iplanrio. Delivered foundational data models covering active debt records, person entities, CDA (Certidões de Dívida Ativa), payment guides and quotas, and associations with properties and related financial data. Performed a targeted data model refactor to simplify the structure by removing an optional linkage and consolidating related representations, preparing the DAM module for data loading and analysis. The work sets the stage for downstream analytics, reporting, and integration with existing systems. No customer-reported defects; all work completed with quality and in alignment with architectural guidelines.
August 2025 monthly summary highlighting delivery across two repositories with a strong emphasis on data standardization, data modeling, and ingestion improvements that enable robust analytics and governance.
August 2025 monthly summary highlighting delivery across two repositories with a strong emphasis on data standardization, data modeling, and ingestion improvements that enable robust analytics and governance.
July 2025 monthly summary for Prefeitura Rio project prefeitura-rio/queries-rj-sms: PCSM Data Ingestion and Modeling Enhancements. Delivered foundational PCSM data pipeline improvements and a new Prescription dataset to consolidate data, enabling richer analytics for mental-health services in Rio de Janeiro.
July 2025 monthly summary for Prefeitura Rio project prefeitura-rio/queries-rj-sms: PCSM Data Ingestion and Modeling Enhancements. Delivered foundational PCSM data pipeline improvements and a new Prescription dataset to consolidate data, enabling richer analytics for mental-health services in Rio de Janeiro.

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