
Worked on the ministryofjustice/analytical-platform-airflow repository to deliver MDSS Data Interval Slicing in Airflow, enabling per-run data slices for incremental data processing. Leveraged Airflow and YAML to introduce DATA_INTERVAL_START and DATA_INTERVAL_END template variables, allowing workflows to load data by interval and improving data accuracy. Enhanced deployment safety by implementing a Docker image security update and a minor version bump, supporting interval testing and reducing deployment risk. Focused on configuration management and CI/CD practices, the work reduced data latency and streamlined workflow execution. The engineering approach emphasized maintainability and reliability, addressing both data processing needs and operational security requirements.
July 2025: Delivered MDSS Data Interval Slicing in Airflow with per-run data slices to enable incremental processing. Introduced DATA_INTERVAL_START and DATA_INTERVAL_END template variables for the MDSS in Airflow workflows, enabling loads by interval. Implemented a Docker image security update and a minor version bump to support interval testing and safer deployments. These changes, tracked in commits 8653209fce897f8c174d3bc7f92929198a357b13 and 46f9cf0c88d7ba5edb764a6946a855b8c5850b21, reduce data latency, improve accuracy, and reduce deployment risk.
July 2025: Delivered MDSS Data Interval Slicing in Airflow with per-run data slices to enable incremental processing. Introduced DATA_INTERVAL_START and DATA_INTERVAL_END template variables for the MDSS in Airflow workflows, enabling loads by interval. Implemented a Docker image security update and a minor version bump to support interval testing and safer deployments. These changes, tracked in commits 8653209fce897f8c174d3bc7f92929198a357b13 and 46f9cf0c88d7ba5edb764a6946a855b8c5850b21, reduce data latency, improve accuracy, and reduce deployment risk.

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