CS-03 — Data platforms · Automation & AI
Consolidation of legacy event data in Snowflake
Python tooling to discover, migrate, reconcile and validate older and newer generations of event tables across hundreds of tenant schemas, with hundreds of millions of records, without loss or duplicates.
- My role
- Development of the migration and validation tooling (Wizeline).
- Period
- Not documented
- Disclosure
- Anonymised details
- Technologies
- PythonSnowflakeSQL
- Last reviewed
- 13 November 2026
Context
Architecture changes and the evolution of the ingestion infrastructure left several generations of event data structures. Historical information was spread across older and newer table formats.
Challenges
- 01Scale of hundreds of tenant schemas and hundreds of millions of records.
- 02Avoiding data loss and accidental duplicates in a production migration.
- 03Missing or inconsistent permissions across schemas.
Solution & architecture
Python tooling that discovers legacy structures, identifies migration candidates, compares coverage between source and target, migrates the history, detects duplicates, validates the migrated records, handles missing permissions and, once validated, removes the obsolete structures.
Key decisions
D-01
Validate before deleting
Obsolete structures are only retired after checking coverage and the absence of duplicates, to preserve historical integrity.
Trade-offs
Not documented yet
Results
Migration runs across hundreds of tenant schemas and hundreds of millions of records, with coverage and duplicate validation.
Lessons learned
Not documented yet
Skills involved: Python, Snowflake, SQL, data migration and reconciliation, data modelling on distributed platforms, operational automation and safe production migrations.
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