Planning-Inspectorate/odw-synapse-workspace
Mar 2026 – Apr 2026
2 Months active
Languages Used
JSONPython
Technical Skills
data engineeringdata transformationnotebook developmentAnonymisationAzureAzure Synapse
Stef Deligia
PROFILE
Stef Deligia
Over a two-month period, contributed to the Planning-Inspectorate/odw-synapse-workspace repository by delivering seven features and resolving two bugs focused on data engineering and governance. Developed enhancements to data ingestion notebooks, streamlining parameter management to accelerate pipeline setup and improve clarity for data engineers. Advanced the anonymisation framework with SHA-256 email hashing, postcode strategies, and REDACTED masking, ensuring deterministic joins and robust data privacy. Implemented Spark-based migration tooling for managed-to-external table conversions, addressing storage scalability and deployment issues. Leveraged Python, PySpark, and Azure Synapse, with comprehensive unit and integration testing to ensure reliability, maintainability, and improved data validation across environments.
Overall Statistics
Feature vs Bugs
78%Features
Repository Contributions
12Total
Bugs
2
Commits
12
Features
7
Lines of code
7,071
Activity Months2
Your Network
71 peopleSame Organization
@planninginspectorate.gov.uk52
Work History
April 2026
11 Commits • 6 Features
Apr 1, 2026April 2026 saw a strong emphasis on data governance, anonymisation, and migration tooling. Delivered enhancements to the anonymisation framework (new package, SHA-256 email hashing, postcode strategy, REDACTED name masking, PIN inspector integration, Purview classifications) with comprehensive unit/integration tests and a DEV-only gating mechanism. Implemented Spark-based migration tooling to convert managed tables to external tables, accompanied by a post-deployment pipeline to resolve LOCATION_ALREADY_EXISTS issues and enable scalable storage. Restructured AIE Document processing to improve harmonisation with added integration tests. Implemented specialism deduplication in pins_inspector to prevent data growth, and fixed a table location bug in curated/harmonised notebooks with added legacy data handling. Upgraded Pydantic to improve data validation and completed multiple code-quality improvements across ETL results and notebooks. Overall impact: stronger data governance, deterministic anonymisation enabling reliable joins on anonymised data, safer migrations, and more stable ETL pipelines across environments. Technologies/skills demonstrated: PySpark/Spark notebooks, Purview classifications, SHA-256 hashing, REDACTED masking strategy, Pydantic v1 compatibility, and notebook/pipeline orchestration across development, testing, and production environments.
11 Commits • 6 Features
Apr 1, 2026April 2026 saw a strong emphasis on data governance, anonymisation, and migration tooling. Delivered enhancements to the anonymisation framework (new package, SHA-256 email hashing, postcode strategy, REDACTED name masking, PIN inspector integration, Purview classifications) with comprehensive unit/integration tests and a DEV-only gating mechanism. Implemented Spark-based migration tooling to convert managed tables to external tables, accompanied by a post-deployment pipeline to resolve LOCATION_ALREADY_EXISTS issues and enable scalable storage. Restructured AIE Document processing to improve harmonisation with added integration tests. Implemented specialism deduplication in pins_inspector to prevent data growth, and fixed a table location bug in curated/harmonised notebooks with added legacy data handling. Upgraded Pydantic to improve data validation and completed multiple code-quality improvements across ETL results and notebooks. Overall impact: stronger data governance, deterministic anonymisation enabling reliable joins on anonymised data, safer migrations, and more stable ETL pipelines across environments. Technologies/skills demonstrated: PySpark/Spark notebooks, Purview classifications, SHA-256 hashing, REDACTED masking strategy, Pydantic v1 compatibility, and notebook/pipeline orchestration across development, testing, and production environments.
April 2026
March 2026
1 Commits • 1 Features
Mar 1, 2026March 2026: Delivered a key feature in Planning-Inspectorate/odw-synapse-workspace that enhances data ingestion usability by updating the notebook template. This change streamlines parameter inputs and outputs, reducing setup time for data pipelines and improving clarity for data engineers. No major bugs fixed in this period. Overall impact includes faster onboarding for data workflows and a solid foundation for templated notebook usage. Technologies/skills demonstrated include notebook templating, parameterization, and focused UX improvements in data ingestion templates.
March 2026
1 Commits • 1 Features
Mar 1, 2026March 2026: Delivered a key feature in Planning-Inspectorate/odw-synapse-workspace that enhances data ingestion usability by updating the notebook template. This change streamlines parameter inputs and outputs, reducing setup time for data pipelines and improving clarity for data engineers. No major bugs fixed in this period. Overall impact includes faster onboarding for data workflows and a solid foundation for templated notebook usage. Technologies/skills demonstrated include notebook templating, parameterization, and focused UX improvements in data ingestion templates.
Activity
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Quality Metrics
Correctness88.2%
Maintainability81.6%
Architecture83.4%
Performance80.0%
AI Usage43.4%
Skills & Technologies
Programming Languages
JSONPython
Technical Skills
AnonymisationAzureAzure SynapseCloud ComputingData EngineeringData ProcessingETLPySparkPythonPython programmingSparkUnit Testingconfiguration managementdata analysisdata anonymisation
Repositories Contributed To
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