Challenges focused on data warehouse migration, ETL pipeline modernization, data quality validation, and analytics platform transitions.
Job titles: Data Engineer, Analytics Engineer, Data Architect, ETL Developer
| Module | Difficulty | Time |
|---|---|---|
| DW Migration: Teradata to Snowflake | Intermediate–Advanced | 60 min |
| Data Source Migration | Intermediate | 60 min |
| ETL Pipeline Modernization | Intermediate–Advanced | 60 min |
| Data Quality & Validation | Intermediate | 45 min |
| SAS to Python/Snowflake | Intermediate–Advanced | 60 min |
| Repository | Compatible Modules |
|---|---|
| uc-dw-migration-teradata-to-snowflake | DW Migration: Teradata to Snowflake, ETL Pipeline Modernization, Data Quality & Validation |
| uc-data-source-migration-legacy-to-modern | Data Source Migration |
- Data-focused audiences (data engineering, analytics, BI teams)
- Workshops showing Devin's ability to understand and transform data schemas, queries, and pipelines
- DW Migration and SAS to Python/Snowflake are particularly relevant for enterprises migrating off legacy analytics platforms
- Data Quality & Validation pairs well with any data migration module as a validation step
- The
uc-dw-migration-teradata-to-snowflakerepo was specifically curated for these challenges