Nike-Inc/spark-expectations
Jul 2025 – Oct 2025
3 Months active
Languages Used
CSVMarkdownPytestPythonYAMLJupyter NotebookSQL
Technical Skills
Data CleaningData QualityDocumentationFile ManagementProject ManagementPython Development
Patrick Miki
PROFILE
Patrick Miki
Worked on the Nike-Inc/spark-expectations repository, delivering features that enhanced data quality, reliability, and observability for Spark-based data pipelines. Developed and integrated a PagerDuty notification system, enabling automated incident creation and real-time alerting from test results, with secure configuration using secret managers. Improved dataset management by standardizing naming conventions and cleaning example resources, while strengthening data quality checks through robust parsing and comprehensive testing. Authored detailed documentation and end-to-end notebooks to support adoption and on-call workflows. Leveraged Python, SQL, and PySpark, focusing on backend development, configuration management, and data engineering to streamline incident response and maintain high data standards.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
6Total
Bugs
1
Commits
6
Features
4
Lines of code
1,833
Activity Months3
Work History
October 2025
2 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for Nike-Inc/spark-expectations: Delivered PagerDuty Notifications Integration to enable real-time incident alerting for Spark Expectations, including documentation of prerequisites, configuration parameters, and an end-to-end example for alert setup and viewing results. The feature ships a testing notebook and example user configuration, facilitating quick adoption by on-call teams. This work improves observability, reduces incident detection and response time for data-quality checks, and strengthens reliability of Spark Expectations deployments.
2 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for Nike-Inc/spark-expectations: Delivered PagerDuty Notifications Integration to enable real-time incident alerting for Spark Expectations, including documentation of prerequisites, configuration parameters, and an end-to-end example for alert setup and viewing results. The feature ships a testing notebook and example user configuration, facilitating quick adoption by on-call teams. This work improves observability, reduces incident detection and response time for data-quality checks, and strengthens reliability of Spark Expectations deployments.
October 2025
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025: Delivered PagerDuty Notification Plugin for Spark-Expectations, enabling automated incident creation and alerting from test results. Key work included secure retrieval of PagerDuty integration keys from secret managers and library configuration updates to fully enable PagerDuty alerts. This improves on-call visibility, accelerates incident response, and strengthens CI/test reliability.
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025: Delivered PagerDuty Notification Plugin for Spark-Expectations, enabling automated incident creation and alerting from test results. Key work included secure retrieval of PagerDuty integration keys from secret managers and library configuration updates to fully enable PagerDuty alerts. This improves on-call visibility, accelerates incident response, and strengthens CI/test reliability.
July 2025
3 Commits • 2 Features
Jul 1, 2025July 2025 performance highlights for Nike-Inc/spark-expectations: delivered key dataset maintenance improvements and reliability enhancements, with targeted fixes and up-to-date documentation. Focused on business value through reliable data loading, robust data quality checks, and clear contributor visibility.
3 Commits • 2 Features
Jul 1, 2025July 2025 performance highlights for Nike-Inc/spark-expectations: delivered key dataset maintenance improvements and reliability enhancements, with targeted fixes and up-to-date documentation. Focused on business value through reliable data loading, robust data quality checks, and clear contributor visibility.
July 2025
Activity
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Quality Metrics
Correctness93.4%
Maintainability91.8%
Architecture91.8%
Performance90.0%
AI Usage30.0%
Skills & Technologies
Programming Languages
CSVJupyter NotebookMarkdownPytestPythonSQLYAML
Technical Skills
API IntegrationBackend DevelopmentConfiguration ManagementData CleaningData EngineeringData QualityDocumentationFile ManagementNotebook DevelopmentNotification SystemsPagerDuty IntegrationProject ManagementPySparkPythonPython Development
Repositories Contributed To
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