Engineering the pipelines behind earth observation science
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Field notes
From remote-sensing labs at NUST to building data pipelines in code, I bring an earth-systems science mindset to every dataset I ingest, model, and analyse.
Credentials
How I work
Principles that guide every pipeline, dataset, and analysis from ingestion through reporting.
Reliable data pipelines
Building reproducible, observable ETL/ELT for satellite imagery — versioned code, automated tests, and documentation so every run is auditable.
Scientific rigor
Grounding remote-sensing analysis in earth-systems science, with transparent methods and reproducible notebooks behind every indicator and report.
Spatial data integrity
Treating spatial databases as products: clean schemas, validated geometries, and secure, efficient access for APIs, web apps, and analysis.
Experience
Career History
GIS Plus Pvt Ltd
2025 — PresentDesign and maintain data pipelines for satellite imagery and vector products, manage PostGIS spatial databases, and collaborate with web developers on schemas that power mapping APIs and applications.
Jugrafiya
2024Built raster and vector processing workflows in Python and Google Earth Engine for land-cover and change-detection analysis, and migrated manual desktop tasks into reproducible, scripted pipelines.
IGIS – NUST
2023Supported earth-observation research — preparing geospatial datasets, running spatial analysis in R and Python, and contributing to scientific reporting on environmental monitoring.
Toolbelt
The languages, geospatial libraries, and infrastructure I lean on to deliver reliable earth-observation systems.