profcomff/dwh-pipelines
Nov 2024 – Sep 2025
3 Months active
Languages Used
PythonSQL
Technical Skills
API IntegrationAirflowData EngineeringETLSQLLogging
Stanislav Roslavtsev
PROFILE
Stanislav Roslavtsev
Worked on the profcomff/dwh-pipelines repository to automate and enhance data workflows supporting timetabling and union member management. Developed Airflow DAGs in Python and SQL to synchronize lecturer data from the data warehouse to the timetable API, automate user and union member joins, and improve data freshness while reducing manual reconciliation. Enhanced observability by adding logging to track processed records and restored critical data-fetching logic to ensure data completeness. Addressed bugs related to variable naming, authorization formatting, and dataset references, resulting in more reliable and maintainable ETL pipelines. Demonstrated strengths in API integration, Airflow orchestration, and robust data engineering practices.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
7Total
Bugs
3
Commits
7
Features
3
Lines of code
153
Activity Months3
Your Network
4 peopleShared Repositories
4
Work History
September 2025
2 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary: Strengthened the profcomff/dwh-pipelines data workflow by enhancing observability for the union_member_download pipeline and restoring critical data-fetching behavior. These changes improve monitoring, data completeness checks, and pipeline reliability, contributing to faster issue diagnosis and higher trust in data deliveries.
2 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary: Strengthened the profcomff/dwh-pipelines data workflow by enhancing observability for the union_member_download pipeline and restoring critical data-fetching behavior. These changes improve monitoring, data completeness checks, and pipeline reliability, contributing to faster issue diagnosis and higher trust in data deliveries.
September 2025
December 2024
3 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for profcomff/dwh-pipelines: Delivered a new Airflow DAG that joins DWH_USER_INFO.info with STG_UNION_MEMBER.union_member to create DM_USER.union_member_join, with upsert on full_name on conflicts. Implemented dataset reference corrections and formatting improvements to ensure trigger correctness and readability. Fixed a bug in the DAG dataset reference to ensure correct STG_UNION_MEMBER.union_member reference and trigger behavior. These changes improve data freshness, accuracy of user data joins, and maintainability of the pipeline.
December 2024
3 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for profcomff/dwh-pipelines: Delivered a new Airflow DAG that joins DWH_USER_INFO.info with STG_UNION_MEMBER.union_member to create DM_USER.union_member_join, with upsert on full_name on conflicts. Implemented dataset reference corrections and formatting improvements to ensure trigger correctness and readability. Fixed a bug in the DAG dataset reference to ensure correct STG_UNION_MEMBER.union_member reference and trigger behavior. These changes improve data freshness, accuracy of user data joins, and maintainability of the pipeline.
November 2024
2 Commits • 1 Features
Nov 1, 2024November 2024: Focused on delivering automated lecturer data synchronization from the data warehouse to the timetable API via Airflow, and stabilizing the send_lecturers flow. Delivered measurable business value through automated data transfer, improved data freshness for timetabling, and reduced manual effort in data reconciliation.
2 Commits • 1 Features
Nov 1, 2024November 2024: Focused on delivering automated lecturer data synchronization from the data warehouse to the timetable API via Airflow, and stabilizing the send_lecturers flow. Delivered measurable business value through automated data transfer, improved data freshness for timetabling, and reduced manual effort in data reconciliation.
November 2024
Activity
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Quality Metrics
Correctness85.8%
Maintainability85.8%
Architecture77.2%
Performance74.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonSQL
Technical Skills
API IntegrationAirflowData EngineeringETLLoggingSQL
Repositories Contributed To
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