NYPL/drb-etl-pipeline
May 2025 – Jul 2025
3 Months active
Languages Used
PythonXSLTSQLYAML
Technical Skills
API IntegrationAWS SSMCloud StorageData EngineeringData ProcessingDatabase Management
Priya Pai
PROFILE
Priya Pai
Priya Pai developed and enhanced the NYPL/drb-etl-pipeline over three months, focusing on building a robust, automated ETL workflow for GRIN data ingestion and processing. She implemented programmatic OAuth authentication using AWS Parameter Store, centralized logging, and modularized batch processing to improve maintainability and security. Her work integrated AWS S3 and SQS for scalable storage and messaging, while Python and SQL powered the core data engineering and ETL logic. By consolidating OCR processing, automating PDF generation with metadata extraction, and introducing stateful error handling, Priya delivered a maintainable pipeline that reduced manual intervention and improved data quality across ingestion workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
18Total
Bugs
0
Commits
18
Features
8
Lines of code
3,020
Activity Months3
Your Network
18 people
Work History
July 2025
9 Commits • 3 Features
Jul 1, 2025Month: 2025-07 — NYPL/drb-etl-pipeline delivered end-to-end GRIN ingestion enhancements, establishing a robust GRINIngestProcess ETL pipeline and a decoupled messaging flow to improve reliability and scalability of GRIN data. Data quality controls and state handling were introduced to reduce downstream errors and manual remediation. The work also included targeted fixes and optimizations to improve maintainability and performance across the ingestion workflow.
9 Commits • 3 Features
Jul 1, 2025Month: 2025-07 — NYPL/drb-etl-pipeline delivered end-to-end GRIN ingestion enhancements, establishing a robust GRINIngestProcess ETL pipeline and a decoupled messaging flow to improve reliability and scalability of GRIN data. Data quality controls and state handling were introduced to reduce downstream errors and manual remediation. The work also included targeted fixes and optimizations to improve maintainability and performance across the ingestion workflow.
July 2025
June 2025
3 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for NYPL/drb-etl-pipeline. Focused on delivering end-to-end GRIN ingestion and OCR-enabled content generation, with automated orchestration to reduce manual steps and improve downstream processing reliability. Highlights include end-to-end GRIN processing pipeline, OCR-enabled PDF generation with metadata extraction, and consolidation of OCR logic into the ETL pipeline.
June 2025
3 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for NYPL/drb-etl-pipeline. Focused on delivering end-to-end GRIN ingestion and OCR-enabled content generation, with automated orchestration to reduce manual steps and improve downstream processing reliability. Highlights include end-to-end GRIN processing pipeline, OCR-enabled PDF generation with metadata extraction, and consolidation of OCR logic into the ETL pipeline.
May 2025
6 Commits • 3 Features
May 1, 2025May 2025 — NYPL/drb-etl-pipeline: Delivered programmatic GRIN OAuth authentication via AWS Parameter Store; overhauled the GRIN ETL pipeline with batch processing, relocation of conversion/download to dedicated modules, and improved state handling with smaller batch sizes; enhanced GRIN Initial Scrape with modularity, batch processing, configurable parameters, and standardized logging; improved error handling for DB insertions and centralized logging to boost observability.
6 Commits • 3 Features
May 1, 2025May 2025 — NYPL/drb-etl-pipeline: Delivered programmatic GRIN OAuth authentication via AWS Parameter Store; overhauled the GRIN ETL pipeline with batch processing, relocation of conversion/download to dedicated modules, and improved state handling with smaller batch sizes; enhanced GRIN Initial Scrape with modularity, batch processing, configurable parameters, and standardized logging; improved error handling for DB insertions and centralized logging to boost observability.
May 2025
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Quality Metrics
Correctness82.8%
Maintainability81.2%
Architecture77.2%
Performance73.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonSQLXSLTYAML
Technical Skills
API IntegrationAWS LambdaAWS S3AWS S3 IntegrationAWS SQSAWS SSMBackend DevelopmentCloud ComputingCloud StorageConfiguration ManagementData EngineeringData ProcessingDatabase ManagementETLETL Development
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