prefeitura-rio/pipelines_rj_sms
Aug 2025 – Oct 2025
3 Months active
Languages Used
Python
Technical Skills
API IntegrationData EngineeringData PipelinesData WarehousingETLMetabase
HamsterGulloso
PROFILE
Hamstergulloso
Worked on the prefeitura-rio/pipelines_rj_sms repository to enhance data extraction and pipeline reliability over a three-month period. Developed scalable improvements for Metabase data pipelines, enabling sliced queries, per-slice processing, and support for databases without unique IDs, while introducing robust date filtering and simplifying task flows. Addressed technical debt by improving code readability and standardizing parameters. Fixed critical issues in BigQuery table and dataset mapping, ensuring accurate data ingestion and expanding extraction coverage with new table configurations. Resolved a key bug in schedule flow parameter generation, improving data integrity and reliability. Utilized Python, BigQuery, and ETL best practices throughout.
Overall Statistics
Feature vs Bugs
60%Features
Repository Contributions
8Total
Bugs
2
Commits
8
Features
3
Lines of code
1,075
Activity Months3
Your Network
18 peopleShared Repositories
18
Christian BasilioMember
Daniel LiraMember
Daniel LiraMember
Daniel LiraMember
Daniel LiraMember
DayaneRamosMember
Gabriel Gazola MilanMember
heriancMember
srtapachecoMember
Work History
October 2025
1 Commits
Oct 1, 2025October 2025: Stabilized schedule flow parameter generation in prefeitura-rio/pipelines_rj_sms by fixing table data access to include IDs, ensuring parameters are populated with accurate information. No new features released this month; the primary work focused on a critical bug fix that enhances data integrity and reliability of scheduling workflows. This change reduces downstream errors and improves trust in automated schedules across the pipeline.
1 Commits
Oct 1, 2025October 2025: Stabilized schedule flow parameter generation in prefeitura-rio/pipelines_rj_sms by fixing table data access to include IDs, ensuring parameters are populated with accurate information. No new features released this month; the primary work focused on a critical bug fix that enhances data integrity and reliability of scheduling workflows. This change reduces downstream errors and improves trust in automated schedules across the pipeline.
October 2025
September 2025
2 Commits • 1 Features
Sep 1, 2025September 2025: Delivered critical reliability and scalability improvements to the Metabase Data Lake ingestion for prefeitura-rio/pipelines_rj_sms. Implemented fixes to ensure data is loaded into the correct BigQuery tables and datasets and expanded extraction coverage with new table IDs and slice configurations, enabling broader analytics and faster onboarding of new data sources.
September 2025
2 Commits • 1 Features
Sep 1, 2025September 2025: Delivered critical reliability and scalability improvements to the Metabase Data Lake ingestion for prefeitura-rio/pipelines_rj_sms. Implemented fixes to ensure data is loaded into the correct BigQuery tables and datasets and expanded extraction coverage with new table IDs and slice configurations, enabling broader analytics and faster onboarding of new data sources.
August 2025
5 Commits • 2 Features
Aug 1, 2025August 2025 monthly summary focusing on delivering scalable data extraction improvements for prefeitura-rio/pipelines_rj_sms and enhancing maintainability of the data extraction pipeline. The work enables sliced queries, per-slice processing, and support for databases without a unique ID, along with robust date filtering, while simplifying task flows and reducing technical debt.
5 Commits • 2 Features
Aug 1, 2025August 2025 monthly summary focusing on delivering scalable data extraction improvements for prefeitura-rio/pipelines_rj_sms and enhancing maintainability of the data extraction pipeline. The work enables sliced queries, per-slice processing, and support for databases without a unique ID, along with robust date filtering, while simplifying task flows and reducing technical debt.
August 2025
Activity
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Quality Metrics
Correctness82.6%
Maintainability85.0%
Architecture78.8%
Performance72.6%
AI Usage22.6%
Skills & Technologies
Programming Languages
Python
Technical Skills
API IntegrationBigQueryData EngineeringData PipelinesData WarehousingETLMetabasePrefectPython
Repositories Contributed To
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