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Curtis Morales

PROFILE

Curtis Morales

Carlos Morales engineered robust data pipelines and governance enhancements across the mozilla/bigquery-etl and mozilla/lookml-generator repositories, focusing on data quality, operational reliability, and maintainability. He refactored deployment logic for external data tables, improved DAG health monitoring, and implemented deduplication fixes for telemetry datasets using Python and SQL. Carlos streamlined data access management and clarified dataset ownership, reducing ambiguity and supporting scalable policy enforcement. His work included deprecating legacy pipelines, enhancing ETL processes, and cleaning up configuration to align with evolving data catalog practices. Throughout, he demonstrated depth in Airflow orchestration, BigQuery engineering, and configuration management, delivering maintainable, production-grade solutions.

Overall Statistics

Feature vs Bugs

81%Features

Repository Contributions

20Total
Bugs
3
Commits
20
Features
13
Lines of code
450
Activity Months8

Work History

September 2025

4 Commits • 3 Features

Sep 1, 2025

September 2025 monthly summary focusing on delivered features, refactors, and governance improvements across two repositories. Highlights include data quality improvements for Quick Suggest, DAG/config simplifications, and ownership cleanup in LookML generation.

August 2025

2 Commits • 1 Features

Aug 1, 2025

Monthly summary for 2025-08 focused on delivering robustness for External Data Options and deprecating legacy metadata in mozilla/bigquery-etl, with emphasis on reliability, maintainability, and alignment with data catalog practices.

June 2025

1 Commits

Jun 1, 2025

Month 2025-06 focused on delivering a high-impact data quality improvement in the BigQuery ETL pipeline. Implemented a deduplication fix for legacy telemetry in the newtab_interactions_hourly dataset by truncating submission timestamps to the second, ensuring multiple client clicks on the same tile within one second are correctly deduplicated. This change improves accuracy of user interaction analytics and reduces data noise in hourly telemetry streams. Commit reference: 4482a42e49ad0a8ccdadf061f39efbda205d6b36 (#7691).

May 2025

6 Commits • 4 Features

May 1, 2025

In May 2025, delivered key features and fixes across mozilla/bigquery-etl and mozilla/telemetry-airflow, focusing on deprecating unused pipelines, clarifying DAG health criteria, correcting scheduling and dependencies, and strengthening data access governance. Highlights include deprecation/removal of the sponsored_tiles_clients_daily pipeline; triage notes clarifying health criteria for experimenter_experiments_import; scheduling and dependency fixes for newtab_historical; expansion of data access governance by granting default dataViewer access to ads_derived for the ads WG and deprecating an aging dataset nt_visits_to_sessions_conversion_factors_daily_v1; and triage notes added to the partybal DAG in telemetry-airflow. These changes reduce maintenance costs, improve data freshness and access control, and provide clearer operational health signals for faster incident response.

March 2025

2 Commits • 1 Features

Mar 1, 2025

March 2025 monthly summary for mozilla/bigquery-etl: Focused on delivering end-to-end improvements to the Newtab Interactions Hourly dataset with backfill support and initialization logic, strengthening data freshness and quality for downstream analytics.

February 2025

1 Commits • 1 Features

Feb 1, 2025

February 2025 for mozilla/bigquery-etl: Delivered a critical improvement to monitoring clarity for the bqetl_public_data_json DAG by defining health as the most recent run's success, enabling past failures to be ignored. This reduces alert noise, speeds incident response, and improves trust in the data pipeline. The work included updating triage instructions (commit 6947714e26266250314764d4031db64c18ea139a, PR #7065) to reflect the new health criteria. No major bug fixes were logged this month in this repository; the enhancement represents a process reliability and monitoring automation win. Technologies demonstrated include Airflow DAG health checks, monitoring instrumentation, and collaborative change management.

December 2024

3 Commits • 2 Features

Dec 1, 2024

December 2024 monthly performance summary: Strengthened data governance and ownership clarity across two core repos (mozilla/bigquery-etl and mozilla/lookml-generator), delivering concrete governance enhancements for ads and revenue datasets that improve data quality, processing configuration, and policy enforcement. The work reduced ownership ambiguity, enabled scalable stewardship, and prepared the data platforms for future governance rules.

November 2024

1 Commits • 1 Features

Nov 1, 2024

In November 2024 for mozilla/bigquery-etl, the focus was on strengthening the deployment pipeline for external data tables by unifying handling and improving reliability and maintainability.

Activity

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Quality Metrics

Correctness93.4%
Maintainability93.0%
Architecture91.4%
Performance91.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

PythonSQLYAMLyaml

Technical Skills

AirflowBigQueryCloud FunctionsConfiguration ManagementData Access ManagementData EngineeringData WarehousingDatabase ManagementDevOpsDocumentationETLSQL

Repositories Contributed To

3 repos

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

mozilla/bigquery-etl

Nov 2024 Sep 2025
8 Months active

Languages Used

PythonyamlYAMLSQL

Technical Skills

AirflowBigQueryCloud FunctionsData EngineeringETLDevOps

mozilla/lookml-generator

Dec 2024 Sep 2025
2 Months active

Languages Used

YAML

Technical Skills

Configuration Management

mozilla/telemetry-airflow

May 2025 May 2025
1 Month active

Languages Used

Python

Technical Skills

DevOpsDocumentation

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