prefeitura-rio/pipelines_rj_smtr
Oct 2024 – Mar 2026
18 Months active
Languages Used
PythonSQLYAMLyamlJinjaShellMarkdownplaintext
Technical Skills
Data EngineeringETLPythonSQLdbtCI/CD
Guilherme Botelho
PROFILE
Guilherme Botelho
Guilherme worked extensively on the prefeitura-rio/pipelines_rj_smtr repository, building and maintaining robust data pipelines for public transport analytics and regulatory reporting. Over 18 months, he engineered features such as GPS and weather data ingestion, trip validation with geofence logic, and subsidy calculation models, focusing on data quality, traceability, and operational reliability. Leveraging Python, SQL, and dbt, Guilherme implemented incremental processing, schema evolution, and automated testing to ensure accurate, timely data for dashboards and compliance. His work addressed complex data integration, validation, and scheduling challenges, resulting in maintainable, scalable pipelines that improved reporting fidelity and supported evolving business requirements.
Overall Statistics
Feature vs Bugs
72%Features
Repository Contributions
141Total
Bugs
20
Commits
141
Features
52
Lines of code
31,724
Activity Months18
Your Network
5 peopleWork History
March 2026
4 Commits • 2 Features
Mar 1, 2026March 2026 performance summary for prefeitura-rio/pipelines_rj_smtr focused on reliability, data quality, and maintainability across Rio flows. Key features delivered include Data Capture Scheduling Enhancements across the Rio Ônibus flows (CAPTURA_VIAGEM_INFORMADA disabled; CAPTURA_REGISTROS_CITTATI recapture moved to hourly) and Trip Validation Enhancements with Geofence Awareness (geofence-aware departure/arrival times, temporal inconsistency indicators, and refined segment data handling) to improve validation accuracy and reporting. Major bugs fixed in the validation pipeline addressed data type correctness and query reliability (casting id_segmento to int64, timestamp parsing improvements, and feed_start_date joins). Overall impact includes higher data reliability, timeliness, and confidence in operational decisions for Rio, supported by stronger data governance and observability. Technologies demonstrated include SQL-based data validation and windowing, geofence logic, schema evolution, and end-to-end pipeline orchestration, with clear changelog and release hygiene.
4 Commits • 2 Features
Mar 1, 2026March 2026 performance summary for prefeitura-rio/pipelines_rj_smtr focused on reliability, data quality, and maintainability across Rio flows. Key features delivered include Data Capture Scheduling Enhancements across the Rio Ônibus flows (CAPTURA_VIAGEM_INFORMADA disabled; CAPTURA_REGISTROS_CITTATI recapture moved to hourly) and Trip Validation Enhancements with Geofence Awareness (geofence-aware departure/arrival times, temporal inconsistency indicators, and refined segment data handling) to improve validation accuracy and reporting. Major bugs fixed in the validation pipeline addressed data type correctness and query reliability (casting id_segmento to int64, timestamp parsing improvements, and feed_start_date joins). Overall impact includes higher data reliability, timeliness, and confidence in operational decisions for Rio, supported by stronger data governance and observability. Technologies demonstrated include SQL-based data validation and windowing, geofence logic, schema evolution, and end-to-end pipeline orchestration, with clear changelog and release hygiene.
March 2026
February 2026
2 Commits • 1 Features
Feb 1, 2026February 2026 (2026-02) – prefeitura-rio/pipelines_rj_smtr: Delivered incremental strategy enhancements for the viagem_planejada_planejamento model, added snapshot-based processing, and improved incremental logic with an id_execucao_dbt column. Implemented a JSON handling fix for trajetos_alternativos, updated the flows.py documentation header (Feb 11, 2026), registered the flow, and added a changelog entry. These changes increase data reliability, reporting fidelity, and governance/traceability for planning insights.
February 2026
2 Commits • 1 Features
Feb 1, 2026February 2026 (2026-02) – prefeitura-rio/pipelines_rj_smtr: Delivered incremental strategy enhancements for the viagem_planejada_planejamento model, added snapshot-based processing, and improved incremental logic with an id_execucao_dbt column. Implemented a JSON handling fix for trajetos_alternativos, updated the flows.py documentation header (Feb 11, 2026), registered the flow, and added a changelog entry. These changes increase data reliability, reporting fidelity, and governance/traceability for planning insights.
January 2026
2 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for prefeitura-rio/pipelines_rj_smtr. Highlights include two primary deliverables: (1) STU Data Capture Flow Enhancement and (2) Temperature Model and Validation Fix, with changelog entries to improve traceability. The work strengthens data quality, reliability, and cross-day consistency, delivering business value through more accurate daily comparisons and safer data validation across external integrations.
2 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for prefeitura-rio/pipelines_rj_smtr. Highlights include two primary deliverables: (1) STU Data Capture Flow Enhancement and (2) Temperature Model and Validation Fix, with changelog entries to improve traceability. The work strengthens data quality, reliability, and cross-day consistency, delivering business value through more accurate daily comparisons and safer data validation across external integrations.
January 2026
December 2025
6 Commits • 3 Features
Dec 1, 2025December 2025 performance summary for prefeitura-rio/pipelines_rj_smtr: Delivered targeted data-model and flow improvements with clear business value. Highlights include: STU data capture enhancements introducing new tables (guia, permisao_empresa_escola, modelo), initial timestamps, and changelog entries, plus a constant name correction for STU_PERMIS_EMPRESA_ESCOLA_TABLE_ID. Fixed vehicle licensing model materialization by refining last_inspection_date handling (within 2025-07-10 to 2025-12-04 window) and adding chassis treatment logic, with flow registrations and changelog updates. Updated Contract Service Abreviado model to use full month names, with changelog and flow registration. Implemented repo hygiene by ignoring internal DBT packages in .gitignore. Disabled SERPRO capture and treatment flows, with accompanying changelog updates. Overall impact: improved data capture accuracy, more reliable licensing data, better time-series readability in outputs, reduced noise in the repo, and strengthened governance. Technologies/skills demonstrated: DBT modeling, ETL workflow orchestration, data modeling and versioned changelogs, flow registration, cross-team collaboration.
December 2025
6 Commits • 3 Features
Dec 1, 2025December 2025 performance summary for prefeitura-rio/pipelines_rj_smtr: Delivered targeted data-model and flow improvements with clear business value. Highlights include: STU data capture enhancements introducing new tables (guia, permisao_empresa_escola, modelo), initial timestamps, and changelog entries, plus a constant name correction for STU_PERMIS_EMPRESA_ESCOLA_TABLE_ID. Fixed vehicle licensing model materialization by refining last_inspection_date handling (within 2025-07-10 to 2025-12-04 window) and adding chassis treatment logic, with flow registrations and changelog updates. Updated Contract Service Abreviado model to use full month names, with changelog and flow registration. Implemented repo hygiene by ignoring internal DBT packages in .gitignore. Disabled SERPRO capture and treatment flows, with accompanying changelog updates. Overall impact: improved data capture accuracy, more reliable licensing data, better time-series readability in outputs, reduced noise in the repo, and strengthened governance. Technologies/skills demonstrated: DBT modeling, ETL workflow orchestration, data modeling and versioned changelogs, flow registration, cross-team collaboration.
November 2025
9 Commits • 5 Features
Nov 1, 2025November 2025 (2025-11) performance highlights for prefeitura-rio/pipelines_rj_smtr: Key features delivered - Public Transport Data Model & Reporting Enhancements: new views and adjusted models to support reporting on fines and vehicle fleet; updated documentation. - Vehicle Inspection Date Handling after License Plate Change: new views, schema changes, exception handling, changelogs, and flows to ensure accurate inspection data after plate updates. - Contract Services & Travel Cost Reporting Enhancements: added data sources and refined SQL queries to improve reporting of travel costs and contract services; included changelogs and flow registrations. - Garage Data Model Simplification: streamlined data structure by removing certain columns and filters; clarified data flow and reporting; changelogs. - Data Processing Tests & Exception Handling Improvements for Ultima_Vistoria: introduced tests for ultima_vistoria metrics, adjusted tests, and enhanced exception handling to improve data processing reliability. Major bugs fixed - SQL/ETL Cleanup for aux_gps_parada: hotfix removing operador column from the garage CTE and updating the flow registration date. - Custo_cloud Data Processing Fixes: corrected partition filters and added timezone handling in custo_cloud model to improve data accuracy and integrity. - Infrastructure Connectivity Updates: updated host IP addresses for main and tracking databases to ensure correct connectivity with changelogs. Overall impact and accomplishments - Significantly improved data quality and reliability across transport reporting and fleet data; enhanced governance with changelogs and flow registrations; robust handling of plate-change impacts on inspections; better alignment with business reporting requirements. Technologies/skills demonstrated - Advanced SQL data modeling and view creation; schema evolution; ETL/flow reliability; timezone handling and exception management; comprehensive testing; changelog/documentation discipline; cross-team collaboration.
9 Commits • 5 Features
Nov 1, 2025November 2025 (2025-11) performance highlights for prefeitura-rio/pipelines_rj_smtr: Key features delivered - Public Transport Data Model & Reporting Enhancements: new views and adjusted models to support reporting on fines and vehicle fleet; updated documentation. - Vehicle Inspection Date Handling after License Plate Change: new views, schema changes, exception handling, changelogs, and flows to ensure accurate inspection data after plate updates. - Contract Services & Travel Cost Reporting Enhancements: added data sources and refined SQL queries to improve reporting of travel costs and contract services; included changelogs and flow registrations. - Garage Data Model Simplification: streamlined data structure by removing certain columns and filters; clarified data flow and reporting; changelogs. - Data Processing Tests & Exception Handling Improvements for Ultima_Vistoria: introduced tests for ultima_vistoria metrics, adjusted tests, and enhanced exception handling to improve data processing reliability. Major bugs fixed - SQL/ETL Cleanup for aux_gps_parada: hotfix removing operador column from the garage CTE and updating the flow registration date. - Custo_cloud Data Processing Fixes: corrected partition filters and added timezone handling in custo_cloud model to improve data accuracy and integrity. - Infrastructure Connectivity Updates: updated host IP addresses for main and tracking databases to ensure correct connectivity with changelogs. Overall impact and accomplishments - Significantly improved data quality and reliability across transport reporting and fleet data; enhanced governance with changelogs and flow registrations; robust handling of plate-change impacts on inspections; better alignment with business reporting requirements. Technologies/skills demonstrated - Advanced SQL data modeling and view creation; schema evolution; ETL/flow reliability; timezone handling and exception management; comprehensive testing; changelog/documentation discipline; cross-team collaboration.
November 2025
October 2025
17 Commits • 6 Features
Oct 1, 2025Month: 2025-10 — Monthly summary for prefeitura-rio/pipelines_rj_smtr focusing on delivering data-quality and pipeline reliability improvements. Key outcomes include new trip validation model with execution context tracking, GPS data handling differentiation, and STU ingestion with schema adjustments enabling reliable daily incremental processing. Additional work delivered temperature data models (INMET and Alerta Rio) with related pipeline enhancements, and cadastre data snapshot integrity fixes. Hotfixes addressed critical correctness issues, and a test suite was added for minimum technology compliance. Overall, this month strengthened data quality, traceability, and operational reliability, enabling trusted analytics and governance.
October 2025
17 Commits • 6 Features
Oct 1, 2025Month: 2025-10 — Monthly summary for prefeitura-rio/pipelines_rj_smtr focusing on delivering data-quality and pipeline reliability improvements. Key outcomes include new trip validation model with execution context tracking, GPS data handling differentiation, and STU ingestion with schema adjustments enabling reliable daily incremental processing. Additional work delivered temperature data models (INMET and Alerta Rio) with related pipeline enhancements, and cadastre data snapshot integrity fixes. Hotfixes addressed critical correctness issues, and a test suite was added for minimum technology compliance. Overall, this month strengthened data quality, traceability, and operational reliability, enabling trusted analytics and governance.
September 2025
9 Commits • 3 Features
Sep 1, 2025September 2025 performance summary for prefeitura-rio/pipelines_rj_smtr: Delivered core data engineering features, improved data quality, and stabilized historical reporting. Implemented new INMET weather data capture, enhanced climate indicators, GPS processing improvements, and addressed travel, subsidy, and historical data issues to boost reliability and business value.
9 Commits • 3 Features
Sep 1, 2025September 2025 performance summary for prefeitura-rio/pipelines_rj_smtr: Delivered core data engineering features, improved data quality, and stabilized historical reporting. Implemented new INMET weather data capture, enhanced climate indicators, GPS processing improvements, and addressed travel, subsidy, and historical data issues to boost reliability and business value.
September 2025
August 2025
12 Commits • 5 Features
Aug 1, 2025Performance-focused monthly summary for 2025-08 covering delivery of major features, data quality updates, and monitoring improvements in prefeitura-rio/pipelines_rj_smtr. Highlights include climate monitoring enhancements, new transactional-date model, strengthened data quality controls, extended subsidy monitoring with alerts, and documentation/test configuration upgrades. These efforts improve data accuracy, timeliness, and business insights for reporting and operations.
August 2025
12 Commits • 5 Features
Aug 1, 2025Performance-focused monthly summary for 2025-08 covering delivery of major features, data quality updates, and monitoring improvements in prefeitura-rio/pipelines_rj_smtr. Highlights include climate monitoring enhancements, new transactional-date model, strengthened data quality controls, extended subsidy monitoring with alerts, and documentation/test configuration upgrades. These efforts improve data accuracy, timeliness, and business insights for reporting and operations.
July 2025
20 Commits • 3 Features
Jul 1, 2025July 2025 performance summary for prefeitura-rio/pipelines_rj_smtr: Delivered critical data quality fixes and new modeling capabilities, enhanced testing, and reduced technical debt. Key outcomes: corrected transaction and indicator parsing, improved vehicle data timestamps and validated tests, stabilized connectivity to databases, introduced a new trip classification model and enhanced subsidy calculations, expanded DBT testing coverage, and performed infrastructure cleanup and deprecation to simplify the project. These changes improve data reliability for reporting, enable more accurate subsidy calculations, and bolster maintainability and onboarding.
20 Commits • 3 Features
Jul 1, 2025July 2025 performance summary for prefeitura-rio/pipelines_rj_smtr: Delivered critical data quality fixes and new modeling capabilities, enhanced testing, and reduced technical debt. Key outcomes: corrected transaction and indicator parsing, improved vehicle data timestamps and validated tests, stabilized connectivity to databases, introduced a new trip classification model and enhanced subsidy calculations, expanded DBT testing coverage, and performed infrastructure cleanup and deprecation to simplify the project. These changes improve data reliability for reporting, enable more accurate subsidy calculations, and bolster maintainability and onboarding.
July 2025
June 2025
11 Commits • 4 Features
Jun 1, 2025June 2025 performance summary for prefeitura-rio/pipelines_rj_smtr emphasizing delivered features, fixes, and impact across GPS data pipeline, subsidy compliance, dashboard, and KM/Finance processing.
June 2025
11 Commits • 4 Features
Jun 1, 2025June 2025 performance summary for prefeitura-rio/pipelines_rj_smtr emphasizing delivered features, fixes, and impact across GPS data pipeline, subsidy compliance, dashboard, and KM/Finance processing.
May 2025
13 Commits • 4 Features
May 1, 2025May 2025 delivered major data-platform enhancements in GPS ingestion, OS workflow, RDO data dictionary, and daily planning validation, while tightening data quality and consistency across pipelines. The updates improve accuracy, reliability, and scalability, enabling more trusted travel planning data and faster onboarding of OS and GPS formats.
13 Commits • 4 Features
May 1, 2025May 2025 delivered major data-platform enhancements in GPS ingestion, OS workflow, RDO data dictionary, and daily planning validation, while tightening data quality and consistency across pipelines. The updates improve accuracy, reliability, and scalability, enabling more trusted travel planning data and faster onboarding of OS and GPS formats.
May 2025
April 2025
11 Commits • 3 Features
Apr 1, 2025April 2025 monthly summary for prefeitura-rio/pipelines_rj_smtr. Focused on delivering reliable data ingestion, traceability, and maintainability to support regulatory reporting and analytics. Key outcomes include end-to-end SERPRO data capture enhancements, traffic data integration with historical snapshotting, and standardized data models with quality checks. Targeted hotfixes improved pipeline stability and data integrity.
April 2025
11 Commits • 3 Features
Apr 1, 2025April 2025 monthly summary for prefeitura-rio/pipelines_rj_smtr. Focused on delivering reliable data ingestion, traceability, and maintainability to support regulatory reporting and analytics. Key outcomes include end-to-end SERPRO data capture enhancements, traffic data integration with historical snapshotting, and standardized data models with quality checks. Targeted hotfixes improved pipeline stability and data integrity.
March 2025
4 Commits • 2 Features
Mar 1, 2025Summary for 2025-03 (prefeitura-rio/pipelines_rj_smtr): Delivered two major capabilities to enhance data accuracy, governance, and operational insight. 1) Bus Trip Monitoring System: introduces end-to-end monitoring of bus trips to improve data quality, track adherence to planned routes/schedules, and provide actionable insights into service performance (commit 0a109bb27ba1b1d08b69984c95b749de6bbfed5b). 2) Data Governance and Quality Enhancements: consolidated data quality improvements across subsidy data validation and testing, added new technology type versioning with validity periods, and standardized column descriptions across DBT models to improve maintainability (commits 79dec47dac806bca7f59d4b97eabc3692820bb75, 7bf56ed8eefb59fd23c9fc45a130f13df8425e36, 6ed51a279d712a5fa7b1414383bd7d717dcc3180). Impact: higher data accuracy, stronger governance, and improved decision-making for operations and subsidy administration; maintainability benefits from standardized documentation. No major bugs fixed this month; effort focused on feature delivery and quality improvements. Technologies/skills demonstrated: DBT, data quality testing, data governance, versioning of tech types, and documentation standardization.
4 Commits • 2 Features
Mar 1, 2025Summary for 2025-03 (prefeitura-rio/pipelines_rj_smtr): Delivered two major capabilities to enhance data accuracy, governance, and operational insight. 1) Bus Trip Monitoring System: introduces end-to-end monitoring of bus trips to improve data quality, track adherence to planned routes/schedules, and provide actionable insights into service performance (commit 0a109bb27ba1b1d08b69984c95b749de6bbfed5b). 2) Data Governance and Quality Enhancements: consolidated data quality improvements across subsidy data validation and testing, added new technology type versioning with validity periods, and standardized column descriptions across DBT models to improve maintainability (commits 79dec47dac806bca7f59d4b97eabc3692820bb75, 7bf56ed8eefb59fd23c9fc45a130f13df8425e36, 6ed51a279d712a5fa7b1414383bd7d717dcc3180). Impact: higher data accuracy, stronger governance, and improved decision-making for operations and subsidy administration; maintainability benefits from standardized documentation. No major bugs fixed this month; effort focused on feature delivery and quality improvements. Technologies/skills demonstrated: DBT, data quality testing, data governance, versioning of tech types, and documentation standardization.
March 2025
February 2025
4 Commits • 1 Features
Feb 1, 2025February 2025: Delivered targeted fixes and documentation enhancements in prefeitura-rio/pipelines_rj_smtr. Implemented Jinja templating fixes for subsidy-related SQL models to ensure correct conditional execution and robust date/version gating, refined data filtering to exclude pre-subsidy records, and standardized schema descriptions across YAMLs with updated changelog. These changes improved data accuracy, processing reliability, and maintainability, directly supporting accurate subsidy reporting and downstream analytics.
February 2025
4 Commits • 1 Features
Feb 1, 2025February 2025: Delivered targeted fixes and documentation enhancements in prefeitura-rio/pipelines_rj_smtr. Implemented Jinja templating fixes for subsidy-related SQL models to ensure correct conditional execution and robust date/version gating, refined data filtering to exclude pre-subsidy records, and standardized schema descriptions across YAMLs with updated changelog. These changes improved data accuracy, processing reliability, and maintainability, directly supporting accurate subsidy reporting and downstream analytics.
January 2025
3 Commits • 2 Features
Jan 1, 2025January 2025 performance summary for prefeitura-rio/pipelines_rj_smtr. Delivered two key features with substantial business impact and executed a critical data integrity fix, reinforced by production-environment readiness and schema improvements. The work improved pricing accuracy, subsidy data fidelity, and dashboard reliability, setting a stronger foundation for upcoming pricing and subsidy enhancements.
3 Commits • 2 Features
Jan 1, 2025January 2025 performance summary for prefeitura-rio/pipelines_rj_smtr. Delivered two key features with substantial business impact and executed a critical data integrity fix, reinforced by production-environment readiness and schema improvements. The work improved pricing accuracy, subsidy data fidelity, and dashboard reliability, setting a stronger foundation for upcoming pricing and subsidy enhancements.
January 2025
December 2024
4 Commits • 3 Features
Dec 1, 2024December 2024: Delivered three feature-driven improvements to the GTFS-based pipelines in prefeitura-rio/pipelines_rj_smtr, strengthening subsidy calculations, data reliability, and serialization performance. Implemented trip invalidation by average speed with a 110 km/h threshold, refactored the GTFS pipeline for chunked processing with enhanced error handling and Discord alerts, expanded data modeling with descriptive columns and fields for transactionless trips and judicial penalties, and optimized content serialization using pandas to_json with robust null handling and encoding.
December 2024
4 Commits • 3 Features
Dec 1, 2024December 2024: Delivered three feature-driven improvements to the GTFS-based pipelines in prefeitura-rio/pipelines_rj_smtr, strengthening subsidy calculations, data reliability, and serialization performance. Implemented trip invalidation by average speed with a 110 km/h threshold, refactored the GTFS pipeline for chunked processing with enhanced error handling and Discord alerts, expanded data modeling with descriptive columns and fields for transactionless trips and judicial penalties, and optimized content serialization using pandas to_json with robust null handling and encoding.
November 2024
9 Commits • 3 Features
Nov 1, 2024November 2024: Delivered substantial pipeline improvements for prefeitura-rio/pipelines_rj_smtr, enhancing GTFS time-slot expansion, aligning subsidy calculations with new regulatory rules (Resolution SMTR 3777/2024), and strengthening data reliability through DBT tests and dbt_expectations integration. Also stabilized GPS testing infrastructure and corrected date handling across subsidies flow and test status messaging. Resulting impact includes higher data granularity, regulatory compliance, improved validation and risk reduction, and clearer failure signaling. Technologies demonstrated include GTFS processing, DBT/dbt_expectations, Python-based ETL, and robust test automation.
9 Commits • 3 Features
Nov 1, 2024November 2024: Delivered substantial pipeline improvements for prefeitura-rio/pipelines_rj_smtr, enhancing GTFS time-slot expansion, aligning subsidy calculations with new regulatory rules (Resolution SMTR 3777/2024), and strengthening data reliability through DBT tests and dbt_expectations integration. Also stabilized GPS testing infrastructure and corrected date handling across subsidies flow and test status messaging. Resulting impact includes higher data granularity, regulatory compliance, improved validation and risk reduction, and clearer failure signaling. Technologies demonstrated include GTFS processing, DBT/dbt_expectations, Python-based ETL, and robust test automation.
November 2024
October 2024
1 Commits • 1 Features
Oct 1, 2024October 2024 — Prefeitura Rio pipelines_rj_smtr: Implemented GPS Data Handling Robustness and Validation Improvements to strengthen data integrity and resilience of the GPS ingestion pipeline. Key changes include: new GPS data check constants; enhanced get_raw task to gracefully handle empty GPS capture responses; dbt tests added for data validation; and refactoring of the sppo_aux_registros_realocacao model to adjust filtering logic. These changes reduce data gaps, improve accuracy of location-based analytics, and enable faster detection of anomalies. Commit linked: c209c39a9de790f627474c4facb6bbbab64f551c. Business value: higher reliability of GPS-derived metrics, safer deployments, and better governance over real-time/location data.
October 2024
1 Commits • 1 Features
Oct 1, 2024October 2024 — Prefeitura Rio pipelines_rj_smtr: Implemented GPS Data Handling Robustness and Validation Improvements to strengthen data integrity and resilience of the GPS ingestion pipeline. Key changes include: new GPS data check constants; enhanced get_raw task to gracefully handle empty GPS capture responses; dbt tests added for data validation; and refactoring of the sppo_aux_registros_realocacao model to adjust filtering logic. These changes reduce data gaps, improve accuracy of location-based analytics, and enable faster detection of anomalies. Commit linked: c209c39a9de790f627474c4facb6bbbab64f551c. Business value: higher reliability of GPS-derived metrics, safer deployments, and better governance over real-time/location data.
Activity
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Quality Metrics
Correctness86.8%
Maintainability84.6%
Architecture82.8%
Performance77.2%
AI Usage23.2%
Skills & Technologies
Programming Languages
JinjaMarkdownPythonSQLShellYAMLplaintextyaml
Technical Skills
API IntegrationAutomationBackend DevelopmentBigQueryCI/CDChangelog ManagementCloud ComputingCloud Data PipelinesCloud Data WarehousingCode OrganizationConfiguration ManagementDBTData AnalysisData CleaningData Engineering
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