Saied F.

Messy spatial data, slow PostGIS queries, or manual GIS workflows eating your team's hours? I build automated, scalable geospatial data pipelines that turn raw geographic data into clean, analysis-ready datasets — so your team spends time on decisions, not data wrangling. Over 13+ years, I've helped startups and enterprise clients in telecom, education, mapping, and location intelligence solve problems like: • Building spatial ETL pipelines with Python (GeoPandas, Shapely, Pandas) and FME • Designing and optimizing PostgreSQL/PostGIS databases — spatial indexing, query tuning, data modeling • Automating geoprocessing workflows that used to take days of manual work • Cleaning, validating, and transforming large spatial datasets (including OpenStreetMap data) • Delivering demographic, market, and network analysis with ArcGIS Pro, Business Analyst, and QGIS • Integrating REST APIs and modern formats like GeoParquet into data workflows What sets me apart: I combine deep GIS knowledge with modern data engineering practices. Most GIS analysts can't build production pipelines; most data engineers can't handle spatial data. I do both — which means you get solutions that are accurate, automated, and maintainable, not one-off scripts that break. Whether you need a one-time spatial analysis, a PostGIS database that actually performs, or a complete geospatial data pipeline, I can help. Send me a message with a short description of your data and what you need it to do — I'll reply with how I'd approach it.