prefeitura-rio/prefect_rj_iplanrio
Oct 2025 – Oct 2025
1 Month active
Languages Used
PythonSQLYAML
Technical Skills
API IntegrationBigQueryCI/CDCloud ConfigurationData EngineeringDevOps
patriciacatandi
PROFILE
Patriciacatandi
Patricia Catandi enhanced the prefeitura-rio/prefect_rj_iplanrio repository by delivering end-to-end improvements to the CRM data pipeline, focusing on data model upgrades and infrastructure modernization. She migrated storage and deployment to BigLake and BigQuery, aligning configurations across development, staging, and production environments for consistency and scalability. Using Python, Prefect, and dbt, Patricia introduced dynamic ID handling, improved logging, and secure token-based access to private repositories. Her work streamlined data processing, improved data integrity, and reduced operational overhead by automating deployments and refining environment variables, demonstrating depth in data engineering and DevOps practices within a modern cloud-based workflow.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
16Total
Bugs
0
Commits
16
Features
2
Lines of code
225
Activity Months1
Work History
October 2025
16 Commits • 2 Features
Oct 1, 2025October 2025 monthly summary for prefeitura-rio/prefect_rj_iplanrio: Delivered end-to-end CRM data-pipeline enhancements and infrastructure modernization, driving data quality, performance, and deployment consistency. No critical user-facing bugs were reported; maintenance tasks focused on log cleanup and observability to support stability. Key work spanned CRM data model upgrades, processing enhancements, and storage/deployment modernization to BigLake/BigQuery with environment-aligned configurations. These efforts culminated in a scalable, reliable CRM workflow with streamlined deployments across dev/stage/prod. Technologies demonstrated include Python, Prefect, BigQuery/BigLake, GCS, dbt, and token-based access to private repos.
16 Commits • 2 Features
Oct 1, 2025October 2025 monthly summary for prefeitura-rio/prefect_rj_iplanrio: Delivered end-to-end CRM data-pipeline enhancements and infrastructure modernization, driving data quality, performance, and deployment consistency. No critical user-facing bugs were reported; maintenance tasks focused on log cleanup and observability to support stability. Key work spanned CRM data model upgrades, processing enhancements, and storage/deployment modernization to BigLake/BigQuery with environment-aligned configurations. These efforts culminated in a scalable, reliable CRM workflow with streamlined deployments across dev/stage/prod. Technologies demonstrated include Python, Prefect, BigQuery/BigLake, GCS, dbt, and token-based access to private repos.
October 2025
Activity
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Quality Metrics
Correctness81.2%
Maintainability82.4%
Architecture71.2%
Performance65.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonSQLYAML
Technical Skills
API IntegrationBigQueryCI/CDCloud ConfigurationData EngineeringDevOpsETLEnvironment VariablesGitHub APILoggingPrefectPythonSQLdbt
Repositories Contributed To
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