ministryofjustice/analytical-platform-airflow
Jul 2025 – Jul 2025
1 Month active
Languages Used
PythonYAML
Technical Skills
AirflowCI/CDCloud EngineeringCloud InfrastructureConfiguration ManagementData Engineering
Dugald Hepburn
PROFILE
Dugald Hepburn
Developed and deployed the CJSM Email Logs Preprocessing workflow for the ministryofjustice/analytical-platform-airflow repository, focusing on scalable log processing using Airflow DAGs. The work involved implementing branching logic, configuring compute resources, and expanding IAM permissions to optimize both security and resource usage. Python and YAML were used to define workflows and environment configurations, supporting both development and production deployments. CI/CD pipelines were maintained and improved through routine updates, including workflow refinements and image tag management, which enhanced deployment reliability. This approach enabled faster, more maintainable processing of CJSM email logs and ensured robust, scalable infrastructure for ongoing data engineering needs.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
15Total
Bugs
0
Commits
15
Features
1
Lines of code
336
Activity Months1
Your Network
436 peopleWork History
July 2025
15 Commits • 1 Features
Jul 1, 2025July 2025: Delivered CJSM Email Logs Preprocessing workflow (Airflow DAGs) for the ministryofjustice/analytical-platform-airflow with development and production deployments, including branching logic, compute resource configurations, expanded IAM permissions, and environment configurations to support scalable log processing. CI/CD pipelines were stabilized through routine workflow updates and image tag management, enabling reliable production deployments and faster iteration cycles.
15 Commits • 1 Features
Jul 1, 2025July 2025: Delivered CJSM Email Logs Preprocessing workflow (Airflow DAGs) for the ministryofjustice/analytical-platform-airflow with development and production deployments, including branching logic, compute resource configurations, expanded IAM permissions, and environment configurations to support scalable log processing. CI/CD pipelines were stabilized through routine workflow updates and image tag management, enabling reliable production deployments and faster iteration cycles.
July 2025
Activity
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Quality Metrics
Correctness90.6%
Maintainability90.6%
Architecture89.4%
Performance81.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonYAML
Technical Skills
AirflowCI/CDCloud EngineeringCloud InfrastructureConfiguration ManagementData EngineeringDevOpsInfrastructure ConfigurationInfrastructure ManagementWorkflow ManagementWorkflow Orchestration
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