Freelancer profile translated to English.
Back to original languageAbout Badre
Geospatial Engineer & Data Engineer
Water · Energy · Environment · Climate
I help companies transform their geospatial data into operational tools: automated pipelines, spatial databases, WebGIS applications, dashboards, simulations, SaaS, and business indicators.
My profile combines two areas of expertise:
- solid IT skills in data/geospatial development, and
- business expertise in hydrology, hydraulics, climate, energy, and environment.
I can work across the entire chain, from raw data to the final application.
Data I process
Satellite: Sentinel-1 SAR, Sentinel-2 optical, hyperspectral, land cover, Google Earth Engine
Climate:ERA5 reanalysis, atmospheric variables, climate time series
Field:SCADA, sensors, hydrological measurements, flow data
Business:Agriculture, water, energy, environment, natural risks, SDG indicators
What I develop:
- Python ETL Pipelines to automate the ingestion, cleaning, standardization, and harmonization of multi-source data.
- Optimized PostgreSQL/PostGIS databases for fast, reliable, and scalable queries.
- WebGIS Applications with MapLibre GL, Leaflet, GeoServer, and FastAPI APIs to visualize, filter, and share data.
- QGIS Plugins with PyQGIS to automate field processing and simplify workflows for teams.
- Hydraulic and hydrological simulations with HEC-RAS, TELEMAC, and Python tools to model flows, floods, and climate impacts.
- Power BI Dashboards and decision-making indicators to track results, compare scenarios, and support decision-making.
Main Stack:Python · PostgreSQL/PostGIS · QGIS/PyQGIS · Google Earth Engine · MapLibre GL · Leaflet · GeoServer · FastAPI · Docker · AWS · Power BI · HEC-RAS · TELEMAC · SLURM
NASA ARSET Certified
French
Native or bilingual
English
Native or bilingual
Arabic
Native or bilingual
Kabyle
Native or bilingual
German
Conversational
Can work on-site
Lyon (up to 50km), Paris (up to 50km), Grenoble (up to 50km), Toulouse (up to 50km)
Experience
- GeonicaSenior Geospatial Software Engineer | Geospatial Engineer | Python GIS DeveloperSOFTWARE PUBLISHINGNovember 2025 - May 2026 (6 months)Lyon, FranceDesign and deployment of a cloud-native geospatial platform for local authorities. Supervised a team of 3 GIS developers.
- Python Backend (Django): Django/Django REST Framework backend design — geospatial data models, REST API for spatial querying and data serving, serializers, migrations, and tests (pytest). Decoupled, service-oriented business logic.
- Cloud-Native Architecture & System Design: Scalable architecture design separating ingestion, spatial storage, processing, and application layers; cloud-optimized formats (COG, GeoParquet), OGC compliant services (WMS/WFS/WMTS), and data cataloging for large-scale efficient access.
- Containerization & Deployment: Multi-service architecture orchestrated via Docker Compose (Django application, PostgreSQL/PostGIS, mapping services, reverse proxy), with multi-stage Dockerfiles for reproducible deployments on client infrastructures. CI/CD pipelines (GitHub Actions) for testing and image building.
- Raster Processing & Remote Sensing: Optical and radar (SAR Sentinel-1) satellite imagery processing pipelines, conversion to COG/GeoParquet via GDAL/Rasterio, and exposure of derived products through the API.
- Spatial Data & ETL: PostgreSQL/PostGIS database (GiST indexing, materialized views); Python ETL pipeline for integrating heterogeneous data with quality controls, reprojection, and automated loading.
Skills:Python · Django · Django REST Framework · REST API · Docker · Docker Compose · CI/CD · cloud-native architecture · system design · PostgreSQL · PostGIS · COG · GeoParquet · SAR / Sentinel-1 · remote sensing · GDAL · Rasterio · OGC (WMS/WFS) · ETL pipeline · GIS · geospatial · team management · Linux - INRAeGeospatial Data Engineer | QGIS Plugin & Copernicus Satellite PipelinesRESEARCHApril 2025 - October 2025 (6 months)Lyon, FranceIndustrialization of a research prototype into a geospatial production tool: plot-level flood risk analysis from Sentinel-2 imagery, deployed to 15+ field users.
- Satellite Pipeline: Dask/xarray workflows on SLURM for processing multi-TB datasets (ERA5-Land, Sentinel-2). Complete Python ETL pipeline: Copernicus/IGN/Theia API ingestion → calibration → reprojection → COG/GeoParquet export. OpenEO integration for standardized access to Sentinel archives.
- Operational QGIS Plugin: PyQGIS development (MVC architecture, multi-threading) automating spectral analysis (NDVI, NDWI, NBR) and flood damage classification with pixel-wise probability maps. Training and documentation for 15+ field users.
- Geospatial Database: PostgreSQL/PostGIS schema partitioned by region, GiST indexing, materialized views — sub-second queries on 10M+ entities.
- Python Package: Transformation of notebooks into a modular package (OOP, pytest, Pydantic). QA/QC: CRS validation, topology, band integrity. Geographically stratified evaluation (precision/recall/F1, probability calibration).
Skills: Python · PyQGIS · QGIS · Dask · xarray · SLURM · Sentinel-2 · GDAL · PostGIS · PostgreSQL · FastAPI · Pydantic · pytest · COG · GeoParquet · scikit-learn · automation · ETL pipeline · remote sensing · geospatial · Linux · cartography - Geospatial AI ConsultancyGeoAI Data Engineer | Satellite Classification & SDG IndicatorsENVIRONMENTALDecember 2024 - July 2025 (7 months)Djeddah, Saudi ArabiaDevelopment of complete geospatial processing chains for large-scale environmental monitoring — from raw Sentinel-2 imagery to validated analytical products in production.
- Land Cover Classification: Sentinel-2 multi-spectral model (Random Forest / XGBoost) from A to Z — multi-band feature engineering, Python raster calculation pipelines, delivery of COG and PostGIS vector products for environmental assessment.
- Vegetation Monitoring: Time series of spectral indices (NDVI/EVI/NBR) with phenology detection (start/end of season) and multi-temporal anomaly detection (MAD, IQR, change vector analysis).
- SDG Indicators: Calculation of SDG 15.3.1 (Land Degradation Neutrality) and SDG 15.4.2 (Mountain Green Cover Index) from Sentinel-2, with reproducible and auditable deliverables aligned with international standards.
- Python Industrialization: Orchestration of automated workflows with Dask/xarray, FastAPI APIs (Pydantic, OpenAPI), Make/Bash supervision under Linux.
Skills: Python · Dask · xarray · Sentinel-2 · GDAL · Random Forest · XGBoost · FastAPI · Pydantic · PostGIS · STAC · COG · GeoParquet · scikit-learn · automation · ETL pipeline · remote sensing · geospatial · Linux · cartography · GIS
Recommendations
Be the first to recommend Badre
Help this freelancer shine by sharing your experience working together.
These freelancer profiles also match your criteria
Agatha Frydrych
Backend Java Software Engineer
4.7
(3)
2
Baptiste Duhen
Fullstack developer
4.6
(4)
5
Amed Hamou
Senior Lead Developer
4
(2)
7
Audrey Champion
Web developer
4.3
(3)
4
Education
- Master of Science, Hydraulic & Civil Engineering (HCE)Grenoble INP - ENSE32021- Conçu des pipelines SIG + Python pour calibrer des modèles hydrauliques 1D et produire des cartes décisionnelles prêtes à l’usage. - Accéléré les simulations via ML (Kriging, XGBoost, régression) pour tester plus de scénarios avec moins de coût calcul. - Fiabilisé les résultats avec analyse d’incertitude (Sobol, propagation) pour une décision environnementale robuste. - Livrables orientés métier : risque inondation, gestion eau/territoire, standardisation des workflows géospatiaux.
- State Engineering Diploma in Hydraulics - Hydraulic Engineering and ManagementÉcole Nationale Supérieure d’Hydraulique (ENSH)2019- Piloté une étude hydro-agricole complète (bassin versant -> irrigation) avec approche data-driven. - Automatisé les traitements ArcPy/Python pour réduire les délais d’analyse et industrialiser la cartographie. - Produit des diagnostics spatiaux à forte valeur (ETc, besoins en eau, aptitude des sols, scénarios d’aménagement). - Approche transférable aux missions Remote Sensing / ML en agriculture, climat et infrastructures ENR.
Certifications
- Fundamentals of Remote SensingThe NASA Applied Remote Sensing Training (ARSET) Program2026