DEFRA/epr-common-data-api
Mar 2026 – Mar 2026
1 Month active
Languages Used
C#
Technical Skills
API developmentEntity FrameworkFluentValidationbackend developmentstreaming data handling
Mike McBain
PROFILE
Mike Mcbain
Mike McBain developed scalable streaming data capabilities across the DEFRA/epr-common-data-api and epr-calculator-service repositories, focusing on backend reliability and maintainability. He implemented NDJSON streaming endpoints with gzip compression and timeout management for PayCal data, enabling efficient, high-throughput data delivery. Using C#, Entity Framework, and FluentValidation, Mike introduced a Common Data API client and DataLoader pattern to support bulk ingestion and refactored core services for improved error handling and observability. He also addressed data integrity by migrating and realigning staging tables in epr-calculator-api, ensuring consistent data processing. His work demonstrated depth in API development, data migration, and streaming architectures.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
2
Lines of code
8,362
Activity Months1
Your Network
61 peopleSame Organization
@esynergy.co.uk14
Shared Repositories
47
Saffoora MohammedMember
sahabudeen syedMember
Hamzah ShakeelMember
Tim PeelMember
Nicholas FeatchMember
Ritesh RamanMember
Jagdip Singh (Eviden)Member
LauraToddEvidenMember
Shilpi GoelMember
Work History
March 2026
3 Commits • 2 Features
Mar 1, 2026March 2026 monthly summary across DEFRA data-api and calculator services. Focused on delivering scalable streaming data capabilities, hardening data integrity, and improving maintainability. Key outcomes include NDJSON streaming endpoints with gzip compression and timeout management for PayCal data; a Common Data API client with NDJSON streaming and a DataLoader for bulk ingestion; a data integrity migration to drop/recreate POM and Organisation staging tables. These changes improved throughput, reliability, and observability, enabling faster data-driven decisions and reduced operational risk. Technologies demonstrated include NDJSON streaming, gzip compression, EF Core Timeouts, FluentValidation, InMemory EF, DataLoader pattern, and improved telemetry.
3 Commits • 2 Features
Mar 1, 2026March 2026 monthly summary across DEFRA data-api and calculator services. Focused on delivering scalable streaming data capabilities, hardening data integrity, and improving maintainability. Key outcomes include NDJSON streaming endpoints with gzip compression and timeout management for PayCal data; a Common Data API client with NDJSON streaming and a DataLoader for bulk ingestion; a data integrity migration to drop/recreate POM and Organisation staging tables. These changes improved throughput, reliability, and observability, enabling faster data-driven decisions and reduced operational risk. Technologies demonstrated include NDJSON streaming, gzip compression, EF Core Timeouts, FluentValidation, InMemory EF, DataLoader pattern, and improved telemetry.
March 2026
Activity
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Quality Metrics
Correctness86.6%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
C#
Technical Skills
API developmentAPI integrationC#Entity FrameworkFluentValidationbackend developmentdata processingdatabase migrationstreaming data handlingunit testing
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline
DEFRA/epr-calculator-service
Mar 2026 – Mar 2026
1 Month active
Languages Used
C#
Technical Skills
API integrationbackend developmentdata processingunit testing
DEFRA/epr-calculator-api
Mar 2026 – Mar 2026
1 Month active
Languages Used
C#
Technical Skills
C#Entity Frameworkdatabase migration