GoogleCloudPlatform/DataflowTemplates
Dec 2025 – Dec 2025
1 Month active
Languages Used
JavaPythonYAML
Technical Skills
Apache BeamIcebergJavaPostgreSQLYAMLdata engineering
Ulada Butsenka
PROFILE
Ulada Butsenka
Developed a YAML-based data migration template for the GoogleCloudPlatform/DataflowTemplates repository, enabling selective transfer of data from Iceberg tables to PostgreSQL. The solution incorporated a configurable data filter, allowing for governance-friendly migrations that reduce unnecessary data movement and streamline ETL processes. Leveraging Apache Beam, Java, and YAML, the work included comprehensive end-to-end integration tests to validate both the migration logic and filter functionality. Documentation scaffolding and CI-readiness were addressed to support production deployment. No major bugs were fixed during this period, with the primary focus on delivering a robust, reusable blueprint for controlled data migration in data engineering workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
799
Activity Months1
Your Network
54 peopleWork History
December 2025
1 Commits • 1 Features
Dec 1, 2025December 2025 — GoogleCloudPlatform/DataflowTemplates: Delivered Iceberg to Postgres Data Migration YAML Template with a Data Filter, accompanied by end-to-end integration tests. No major bugs fixed in this period. Impact: enables governance-friendly, selective data migration from Iceberg to Postgres, accelerating data availability and reducing ETL scope. Technologies/skills demonstrated: YAML templating for data pipelines, Iceberg and Postgres integration, and integration testing.
1 Commits • 1 Features
Dec 1, 2025December 2025 — GoogleCloudPlatform/DataflowTemplates: Delivered Iceberg to Postgres Data Migration YAML Template with a Data Filter, accompanied by end-to-end integration tests. No major bugs fixed in this period. Impact: enables governance-friendly, selective data migration from Iceberg to Postgres, accelerating data availability and reducing ETL scope. Technologies/skills demonstrated: YAML templating for data pipelines, Iceberg and Postgres integration, and integration testing.
December 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
JavaPythonYAML
Technical Skills
Apache BeamIcebergJavaPostgreSQLYAMLdata engineering
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