hmcts/ARIAMigration-Databrick
Apr 2025 – Nov 2025
8 Months active
Languages Used
BashBinaryPythonSQLShellYAMLCSSHTML
Technical Skills
ADLSApache SparkAuthenticationAzureAzure DatabricksAzure DevOps
AndrewMcDevittHMCTS
PROFILE
Andrewmcdevitthmcts
Andrew McDevitt engineered robust data processing and deployment automation for the hmcts/ARIAMigration-Databrick repository, delivering end-to-end pipelines for appeals and payment workflows. He implemented parameterized Azure Functions, Databricks workflows, and CI/CD pipelines using Python, SQL, and YAML, focusing on secure, repeatable deployments across multiple environments. His work included modernizing packaging with PyPI wheels, integrating Azure Key Vault for secret management, and enhancing error handling and observability. By refactoring code for maintainability and introducing automated testing and rollback capabilities, Andrew improved release stability, data integrity, and operational efficiency, demonstrating depth in cloud engineering and data pipeline governance throughout the project.
Overall Statistics
Feature vs Bugs
62%Features
Repository Contributions
660Total
Bugs
127
Commits
660
Features
203
Lines of code
67,155
Activity Months8
Your Network
185 people
Work History
November 2025
1 Commits
Nov 1, 2025Monthly work summary for 2025-11 focusing on delivering robustness improvements and a critical bug fix for the ARIAMigration-Databrick project. Emphasizes business value by increasing reliability of data processing and reducing failure handling overhead.
1 Commits
Nov 1, 2025Monthly work summary for 2025-11 focusing on delivering robustness improvements and a critical bug fix for the ARIAMigration-Databrick project. Emphasizes business value by increasing reliability of data processing and reducing failure handling overhead.
November 2025
October 2025
56 Commits • 18 Features
Oct 1, 2025October 2025 — hmcts/ARIAMigration-Databrick: Focused on stabilizing and modernizing the build+deploy pipeline, migrating packaging tooling to UV and adopting PyPI wheels, and accelerating delivery with CI/CD improvements. Delivered packaging/tooling modernization, reliable wheel-based deployments, and runtime/runtime-data access optimizations that reduce operational risk and enable faster iterations.
October 2025
56 Commits • 18 Features
Oct 1, 2025October 2025 — hmcts/ARIAMigration-Databrick: Focused on stabilizing and modernizing the build+deploy pipeline, migrating packaging tooling to UV and adopting PyPI wheels, and accelerating delivery with CI/CD improvements. Delivered packaging/tooling modernization, reliable wheel-based deployments, and runtime/runtime-data access optimizations that reduce operational risk and enable faster iterations.
September 2025
15 Commits • 3 Features
Sep 1, 2025September 2025 monthly summary for hmcts/ARIAMigration-Databrick. Delivered end-to-end payment-pending data processing pipelines and workflows on Databricks, including active appeals data pipelines, queues, task orchestration, and publishing to Event Hubs. Added active data transformation and CCD call results configurations to support robust data processing workflows. Ingested reference data asset for Scottish bail cases (Scottish_Bailsfile.csv) to enable accurate reference data processing. Implemented targeted bug fixes in active data transformation workflows to correct typos, parameter naming, dependencies, and full_refresh behavior. Improved deployment/config hygiene with YAML-based naming conventions and dependency management for maintainable pipelines.
15 Commits • 3 Features
Sep 1, 2025September 2025 monthly summary for hmcts/ARIAMigration-Databrick. Delivered end-to-end payment-pending data processing pipelines and workflows on Databricks, including active appeals data pipelines, queues, task orchestration, and publishing to Event Hubs. Added active data transformation and CCD call results configurations to support robust data processing workflows. Ingested reference data asset for Scottish bail cases (Scottish_Bailsfile.csv) to enable accurate reference data processing. Implemented targeted bug fixes in active data transformation workflows to correct typos, parameter naming, dependencies, and full_refresh behavior. Improved deployment/config hygiene with YAML-based naming conventions and dependency management for maintainable pipelines.
September 2025
August 2025
4 Commits • 1 Features
Aug 1, 2025August 2025 performance summary for hmcts/ARIAMigration-Databrick highlighting delivery of a critical environment alignment feature, targeted bug fixes in the GOLD_PAYMENT_PENDING_JSON workflow, and restoration of notebooks/metadata to maintain stable migration operations. These actions improved data integrity, workflow reliability, and deployment consistency across DBFS environments.
August 2025
4 Commits • 1 Features
Aug 1, 2025August 2025 performance summary for hmcts/ARIAMigration-Databrick highlighting delivery of a critical environment alignment feature, targeted bug fixes in the GOLD_PAYMENT_PENDING_JSON workflow, and restoration of notebooks/metadata to maintain stable migration operations. These actions improved data integrity, workflow reliability, and deployment consistency across DBFS environments.
July 2025
21 Commits • 12 Features
Jul 1, 2025Month: 2025-07. Key outcomes across hmcts/ARIAMigration-Databrick include delivery of end-to-end deployment automation for staging and sandbox environments, enhanced pipeline resilience, and targeted fixes that improve multi-env reliability. Delivered deployment pipeline re-run capability to accelerate recovery from failures and enable safer rollbacks. Implemented Deploy to staging and staging deployment execution workflows to ensure consistent updates in staging. Expanded sandbox coverage by deploying to sbox and sbox00, enabling early validation. Fixed critical issues: incorrect DAB stg00 host corrected with re-deploy validation; removed tenant_url from multi-env pipelines to avoid cross-env leakage; stg_aria parameters were commented out to restrict to staging only; minor typo fix. Updated CI/CD configuration for main/master and PR triggers to standardize naming and reduce unintended runs. Performed code cleanup and deployment/config tweaks to simplify deployments by removing legacy flags. These changes deliver business value by faster releases, reduced downtime, better environment parity, and improved governance for deployment pipelines.
21 Commits • 12 Features
Jul 1, 2025Month: 2025-07. Key outcomes across hmcts/ARIAMigration-Databrick include delivery of end-to-end deployment automation for staging and sandbox environments, enhanced pipeline resilience, and targeted fixes that improve multi-env reliability. Delivered deployment pipeline re-run capability to accelerate recovery from failures and enable safer rollbacks. Implemented Deploy to staging and staging deployment execution workflows to ensure consistent updates in staging. Expanded sandbox coverage by deploying to sbox and sbox00, enabling early validation. Fixed critical issues: incorrect DAB stg00 host corrected with re-deploy validation; removed tenant_url from multi-env pipelines to avoid cross-env leakage; stg_aria parameters were commented out to restrict to staging only; minor typo fix. Updated CI/CD configuration for main/master and PR triggers to standardize naming and reduce unintended runs. Performed code cleanup and deployment/config tweaks to simplify deployments by removing legacy flags. These changes deliver business value by faster releases, reduced downtime, better environment parity, and improved governance for deployment pipelines.
July 2025
June 2025
143 Commits • 51 Features
Jun 1, 2025June 2025 performance summary for hmcts/ARIAMigration-Databrick. Key features and improvements delivered: - Parameterized Azure Function and bail logic to improve configurability and maintainability. Commits: 1d3a4ebcd4f63a43414caab2cf2232a57cf756d3; 66a749cff97c3b2e22d0ecc171f11b1c8fe1a735. - Storage reference updates: ABFS to ABFSS, local storage usage, and HTML storage account naming fixes to improve reliability. Commits: 69b781022f2cd4929df3d97360ab56928ec88727; 64eac8074af37300178554d21aa38e51c3871b8c; 461e410f9f07acc440d1e50da554269a812b0f9e. - Pipeline automation and cleanup: automatic pipeline triggering on changes and removal of legacy code paths to accelerate delivery. Commits: 870d45c6f3bf475b3e4a2824cd305c8e665f6d5b; 9fb9f792c5f5b8b9cc348f8d8c48d20517fe301c. - SAS token and secret management enhancements: SAS token usage, CLI-based secret creation, pulling secrets from KV, and deployment debugging support. Commits: 3e5cbbf39e5dd7df75c3c662743c9c764c69cd78; 5ded093cc37ab64ec4c7ffd6ddaa5e04d9c07d36; b289e51b0c2c83f20c853d461ced42ac2b1e2ecc; d904cf8f7fdba1ae752edeff7fe90ba9d97a3eeb; a9b01ff5a29dc8045962614ce697d9180b4ea71d. - Observability and testing: added logging steps, FP segmentation refinements, and expanded ARM path end-to-end tests and test curation coverage. Commits: c06c14285a1ff6ece83f195311a23ba4c2e8637b; 20b866fedeeb07746d867954b6ade0b48f3f55e4; 5a09b9567d875e4ee3a1b46ab062b4238b52e44d; 615a1e39a095b82941ad0b2801b7ba9717190fe9; a2c52ede895d60cf167ff40f006d165d5016784a; c0e8e3c084a7784f47e1bb1fb82aa1eb74e7cd0e. Major bugs fixed: - Reverted Python wheel to 0.0.1 due to compatibility issues, avoiding downstream breakages. Commit: 503492a5856bca4ee251cbbe79feab475440bd05. - Audit path and table naming fixes to prevent data overwrites and ensure correct EH Audit data paths. Commits: dfa5feed2a6fea0990820b7a02dcb227cad249ee; d564bd61cc106624330875fc7a7f9b87a977ef6c; b7c935e8120d801e8bc7e1dfbf06959f7d894e7e. - Azure Function fixes and subdir handling with added logging to verify subdir paths, reducing deployment and runtime failures. Commits: ae5be299a44bb1e45197c2b2e5185b44637f4b63; e48c93bb43c80cdd97a86ebf20a2a4f9e209defb; 022cf110a8d1b20fdbfd33d7609ff3cc80ac5ae9. - Closing bracket and autoloader path issues mitigated by fixes to syntax and filepath handling; removal of stale code paths. Commits: 882f5f546e0b8cdb310f03331243f7f28508556e; e7df64c9ef821b0d4440caa615a7f49825c39fb3. - General code quality and typo fixes across the pipeline and dashboards to stabilize releases. Commits: 317454381dfa2220acea90efd9fa9aad23a2ce6e; 665656f9da0ce2ba527417e107f44ee3a3cd1786. Overall impact and accomplishments: - Strengthened release stability, security posture, and governance across the ARIA Migration Databrick workflow. - Improved configurability, data-path reliability, and automated CI/CD, enabling faster delivery with fewer manual interventions. - Enhanced observability and testing coverage, supporting quicker incident diagnosis and higher confidence in production runs. Technologies/skills demonstrated: - Azure Functions configuration and bail logic parametrization; ABFSS storage integration; KV-backed secret management and SAS token workflows. - Data engineering pipeline governance: automated triggers, pipeline cleanup, and environment-aware TD/FTA/ARM flows; autoloader and dashboard integration. - Observability, testing, and debugging: added logging, FP segmentation refinements, E2E ARM tests, and test curation.
June 2025
143 Commits • 51 Features
Jun 1, 2025June 2025 performance summary for hmcts/ARIAMigration-Databrick. Key features and improvements delivered: - Parameterized Azure Function and bail logic to improve configurability and maintainability. Commits: 1d3a4ebcd4f63a43414caab2cf2232a57cf756d3; 66a749cff97c3b2e22d0ecc171f11b1c8fe1a735. - Storage reference updates: ABFS to ABFSS, local storage usage, and HTML storage account naming fixes to improve reliability. Commits: 69b781022f2cd4929df3d97360ab56928ec88727; 64eac8074af37300178554d21aa38e51c3871b8c; 461e410f9f07acc440d1e50da554269a812b0f9e. - Pipeline automation and cleanup: automatic pipeline triggering on changes and removal of legacy code paths to accelerate delivery. Commits: 870d45c6f3bf475b3e4a2824cd305c8e665f6d5b; 9fb9f792c5f5b8b9cc348f8d8c48d20517fe301c. - SAS token and secret management enhancements: SAS token usage, CLI-based secret creation, pulling secrets from KV, and deployment debugging support. Commits: 3e5cbbf39e5dd7df75c3c662743c9c764c69cd78; 5ded093cc37ab64ec4c7ffd6ddaa5e04d9c07d36; b289e51b0c2c83f20c853d461ced42ac2b1e2ecc; d904cf8f7fdba1ae752edeff7fe90ba9d97a3eeb; a9b01ff5a29dc8045962614ce697d9180b4ea71d. - Observability and testing: added logging steps, FP segmentation refinements, and expanded ARM path end-to-end tests and test curation coverage. Commits: c06c14285a1ff6ece83f195311a23ba4c2e8637b; 20b866fedeeb07746d867954b6ade0b48f3f55e4; 5a09b9567d875e4ee3a1b46ab062b4238b52e44d; 615a1e39a095b82941ad0b2801b7ba9717190fe9; a2c52ede895d60cf167ff40f006d165d5016784a; c0e8e3c084a7784f47e1bb1fb82aa1eb74e7cd0e. Major bugs fixed: - Reverted Python wheel to 0.0.1 due to compatibility issues, avoiding downstream breakages. Commit: 503492a5856bca4ee251cbbe79feab475440bd05. - Audit path and table naming fixes to prevent data overwrites and ensure correct EH Audit data paths. Commits: dfa5feed2a6fea0990820b7a02dcb227cad249ee; d564bd61cc106624330875fc7a7f9b87a977ef6c; b7c935e8120d801e8bc7e1dfbf06959f7d894e7e. - Azure Function fixes and subdir handling with added logging to verify subdir paths, reducing deployment and runtime failures. Commits: ae5be299a44bb1e45197c2b2e5185b44637f4b63; e48c93bb43c80cdd97a86ebf20a2a4f9e209defb; 022cf110a8d1b20fdbfd33d7609ff3cc80ac5ae9. - Closing bracket and autoloader path issues mitigated by fixes to syntax and filepath handling; removal of stale code paths. Commits: 882f5f546e0b8cdb310f03331243f7f28508556e; e7df64c9ef821b0d4440caa615a7f49825c39fb3. - General code quality and typo fixes across the pipeline and dashboards to stabilize releases. Commits: 317454381dfa2220acea90efd9fa9aad23a2ce6e; 665656f9da0ce2ba527417e107f44ee3a3cd1786. Overall impact and accomplishments: - Strengthened release stability, security posture, and governance across the ARIA Migration Databrick workflow. - Improved configurability, data-path reliability, and automated CI/CD, enabling faster delivery with fewer manual interventions. - Enhanced observability and testing coverage, supporting quicker incident diagnosis and higher confidence in production runs. Technologies/skills demonstrated: - Azure Functions configuration and bail logic parametrization; ABFSS storage integration; KV-backed secret management and SAS token workflows. - Data engineering pipeline governance: automated triggers, pipeline cleanup, and environment-aware TD/FTA/ARM flows; autoloader and dashboard integration. - Observability, testing, and debugging: added logging, FP segmentation refinements, E2E ARM tests, and test curation.
May 2025
112 Commits • 30 Features
May 1, 2025May 2025 performance highlights for hmcts/ARIAMigration-Databrick: Key features delivered include Autoloader Notebook Enhancements and Cleanup (queryNames, checkpoint location, config cleanups), SAS Token Fix, Bails CI/CD Workflows Integration, Dashboard and Autoloader Queries Cleanup with YAML Workflow Management, JOH Deployment and Infra Test Suite, EH Data Path Update, and New HTML Template with Dynamic Creation and Validation. Additional improvements include Deployment/CI enhancements, Infrastructure Config Changes, and Packaging/Deployment workflow cleanup with ZipDeploy and ArchiveFiles. Major bugs fixed include SAS token value correction, syntax and lint fixes, loop/cyclical dependency fixes, environment detection logic fixes for sbox, naming convention fixes, dynamic host passing implementation, and environment-limited deployment constraints. Overall impact: more reliable data ingestion, secure, repeatable deployments across environments, and better observability through debugging/validation. Technologies/skills demonstrated: Databricks, Spark, Python notebooks, YAML-based CI/CD workflows, Infrastructure as Code (IaC), packaging and deployment tooling (zipDeploy, ArchiveFiles), debugging and validation tooling, and parameterization.
112 Commits • 30 Features
May 1, 2025May 2025 performance highlights for hmcts/ARIAMigration-Databrick: Key features delivered include Autoloader Notebook Enhancements and Cleanup (queryNames, checkpoint location, config cleanups), SAS Token Fix, Bails CI/CD Workflows Integration, Dashboard and Autoloader Queries Cleanup with YAML Workflow Management, JOH Deployment and Infra Test Suite, EH Data Path Update, and New HTML Template with Dynamic Creation and Validation. Additional improvements include Deployment/CI enhancements, Infrastructure Config Changes, and Packaging/Deployment workflow cleanup with ZipDeploy and ArchiveFiles. Major bugs fixed include SAS token value correction, syntax and lint fixes, loop/cyclical dependency fixes, environment detection logic fixes for sbox, naming convention fixes, dynamic host passing implementation, and environment-limited deployment constraints. Overall impact: more reliable data ingestion, secure, repeatable deployments across environments, and better observability through debugging/validation. Technologies/skills demonstrated: Databricks, Spark, Python notebooks, YAML-based CI/CD workflows, Infrastructure as Code (IaC), packaging and deployment tooling (zipDeploy, ArchiveFiles), debugging and validation tooling, and parameterization.
May 2025
April 2025
308 Commits • 88 Features
Apr 1, 2025April 2025 highlights: Delivered substantialDatabricks asset and CI/CD workflow improvements under hmcts/ARIAMigration-Databrick. The work focused on enabling reliable, repeatable deployment of Databricks assets, expanding deployment coverage to ingest02 workspace, and strengthening pipeline testing and observability. Key outcomes include: the Databricks Asset Bundles CICD integration (ARIA_DABs) with directory restructuring and updated bundle commands; deployment stage added with refreshed PAT variables in ADO to support re-testing; Brew-based CI changes to replace pip and persist Brew shell across steps; CI reliability and path hygiene improvements (working directory validations, notebook_paths updates, and YAML restructuring); and creation of Databricks Pipelines & Workflows with initial test scaffolding and ecosystem readiness for secret management and debugging. Effective collaboration and clear commit traceability across CI/CD, YAML, and Databricks configurations.
April 2025
308 Commits • 88 Features
Apr 1, 2025April 2025 highlights: Delivered substantialDatabricks asset and CI/CD workflow improvements under hmcts/ARIAMigration-Databrick. The work focused on enabling reliable, repeatable deployment of Databricks assets, expanding deployment coverage to ingest02 workspace, and strengthening pipeline testing and observability. Key outcomes include: the Databricks Asset Bundles CICD integration (ARIA_DABs) with directory restructuring and updated bundle commands; deployment stage added with refreshed PAT variables in ADO to support re-testing; Brew-based CI changes to replace pip and persist Brew shell across steps; CI reliability and path hygiene improvements (working directory validations, notebook_paths updates, and YAML restructuring); and creation of Databricks Pipelines & Workflows with initial test scaffolding and ecosystem readiness for secret management and debugging. Effective collaboration and clear commit traceability across CI/CD, YAML, and Databricks configurations.
Activity
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Quality Metrics
Correctness84.0%
Maintainability85.4%
Architecture79.4%
Performance75.0%
AI Usage20.2%
Skills & Technologies
Programming Languages
BashBinaryCSSCSVHTMLJSONJupyter NotebookPythonSQLShell
Technical Skills
ADLSApache SparkAsync ProgrammingAsyncIOAsyncioAuthenticationAutoloaderAzureAzure Blob StorageAzure CLIAzure Data Lake StorageAzure DatabricksAzure DevOpsAzure Event HubAzure Event Hubs
Repositories Contributed To
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