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Data Engineering
Cross-Platform Spatial Data Sync
Designed and implemented automated ETL pipelines that synchronized real-time spatial data across INCMS, DCS, and ArcGIS Enterprise, achieving 100% data integrity and eliminating manual reconciliation.
Overview
A cross-platform spatial data synchronization system built with Python and ArcPy. Features automated ETL pipelines, audit tables, and branched versioning support for multi-user editing.
Tech Stack
PythonArcPyPostgreSQLOracle SDEArcGIS Enterprise
Architecture
Source Systems
INCMS, DCS
ETL Layer
Python + ArcPy
Intermediate DB
PostgreSQL + audit tables
Validation
Data integrity checks
Target
ArcGIS Enterprise, Oracle SDE
Topics
python
etl
gis
spatial-data
postgresql
oracle
Engineering Challenges
Synchronizing spatial data across three platforms with different schemas, projections, and editing workflows while maintaining 100% data integrity.
Lessons Learned
Audit tables are essential for traceability. Schema design upfront saves weeks of debugging. Branched versioning is critical for multi-user spatial editing.