mozilla/bigquery-etl
Apr 2026 – Apr 2026
1 Month active
Languages Used
Python
Technical Skills
PythonSQLdata analysisdata engineeringdebugging
scottbedwell
PROFILE
Scottbedwell
Worked on the mozilla/bigquery-etl repository to enhance website conversion analytics by deploying a web-based conversion event tracking source, shifting attribution from physical store to website interactions. Addressed data quality issues by fixing timestamp inaccuracies in the Meta Conversions API, utilizing BigQuery SQL’s GREATEST function to ensure event times align with ad clicks and prevent future-dated events. Introduced debug logging to improve observability and streamline troubleshooting for Meta payloads. Leveraged Python and SQL for robust data engineering and debugging, resulting in more reliable event sequencing, improved marketing attribution, and enhanced monitoring capabilities for website-driven conversion tracking and analytics workflows.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
18
Activity Months1
Work History
April 2026
2 Commits • 1 Features
Apr 1, 2026April 2026: Delivered key features and fixes in mozilla/bigquery-etl, driving accurate website conversion attribution and robust event timing. Key items: - Web-based Conversion Event Tracking Source Change deployed (WEBSITE) to reflect website-driven interactions and improve website conversion tracking. (Commit aeb282ab3900555bbda97a593309bab5dce6ceea) - Meta Conversions API timestamp accuracy fix using GREATEST and added debug logging to aid troubleshooting. (Commit 63c11e749ebef531ae5e704083bff377c93ad9f1) Impact: - Improved data quality for website conversion analytics and marketing attribution. - Fewer timestamp-related errors (e.g., future-dated events) and more reliable event sequencing. - Improved observability and debugging capability for Meta payloads. Technologies/skills demonstrated: - BigQuery SQL (GREATEST), event_time calculation, and robust data engineering patterns. - Logging instrumentation for API integrations. - Collaborative development (co-authored-by).
2 Commits • 1 Features
Apr 1, 2026April 2026: Delivered key features and fixes in mozilla/bigquery-etl, driving accurate website conversion attribution and robust event timing. Key items: - Web-based Conversion Event Tracking Source Change deployed (WEBSITE) to reflect website-driven interactions and improve website conversion tracking. (Commit aeb282ab3900555bbda97a593309bab5dce6ceea) - Meta Conversions API timestamp accuracy fix using GREATEST and added debug logging to aid troubleshooting. (Commit 63c11e749ebef531ae5e704083bff377c93ad9f1) Impact: - Improved data quality for website conversion analytics and marketing attribution. - Fewer timestamp-related errors (e.g., future-dated events) and more reliable event sequencing. - Improved observability and debugging capability for Meta payloads. Technologies/skills demonstrated: - BigQuery SQL (GREATEST), event_time calculation, and robust data engineering patterns. - Logging instrumentation for API integrations. - Collaborative development (co-authored-by).
April 2026
Activity
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Quality Metrics
Correctness100.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
PythonSQLdata analysisdata engineeringdebugging
Repositories Contributed To
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