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MISSION BRIEF / Data

SQL-to-PostgreSQL Data Migration

A Python console for mapping, transforming and monitoring a large SQL-to-PostgreSQL migration.

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Sanitized engineering overview. The diagram is an original redraw with generic labels; business identifiers and production details are omitted.

MY ROLE

Engineering contribution to a team migration and its Python console, including source-to-target field mapping and data transformation.

The problem

Move a large dataset between different schemas while preserving relationships and validating how source fields map to the PostgreSQL target.

Architecture

Migration pathPrerequisites / controlled writesRead-only
SOURCEMIGRATION PIPELINETARGETPython migration consoleControl · monitor · report · map · tuneschemarulesLegacy SQL databaseRead-only source1Environment setupMigration configuration2Field mappingSource-to-target rules3Reference importPrerequisite data4ExtractionRead source records5Data preparationClean · transform · batch6LoaderApply field mappingsStaging databaseRetain migration state7Migration workerExecute migration steps8Repair toolsResolve inconsistencies9ReconciliationCompare source and targetTarget APIApplication interfacePostgreSQLTarget database
Legacy SQL source → PostgreSQL target

Python console · control, monitor, report, map and tune

Staging retains migration state; reconciliation reads and compares records.

TRACE A STAGE

Select a stage to inspect its connections.

Public architecture overview · generic labels and illustrative connections.

Engineering decisions

  • Define explicit source-to-target field mappings before loading records.
  • Separate extraction and data preparation from target writes.
  • Transform and batch data through a staging layer before migration execution.
  • Centralize migration control, monitoring and report generation in the Python console.
  • Use the console to tune migration performance alongside mapping and transformation work.
  • Keep reconciliation read-only and resolve inconsistencies through a separate repair step.

Challenges

  • Mapping fields and relationships between different database schemas.
  • Transforming a large dataset into the target representation.
  • Coordinating staging, execution, repair and reconciliation without exposing confidential business data.

The solution

A complete Python console brings migration control, progress monitoring, report generation, field and data mapping, transformation and performance tuning into one tool. The staged workflow separates extraction, preparation and execution, retaining migration state for repair and reconciliation.

The result

The team built the Python migration console, mapped source fields and transformed the data for PostgreSQL. The tool supports monitoring, reports and performance tuning; this overview does not publish customer data, operational volumes or measured performance claims.

Tech stack

  • Python
  • SQL
  • PostgreSQL