FEATURE — POINT DATA

Alexander
Hernes

Full-Stack Geospatial Data Engineer

LOCATION Sacramento, CA · 38.58°N, 121.49°W
RECORDS PROCESSED 10,000+ gauges · tens of millions of records
CURRENT POSITION Computer Scientist, USGS California Water Science Center
alek.hernes@gmail.com LinkedIn GitHub

Field notes — Work History

JUN 2024 — PRESENT CA WATER SCIENCE CENTER

Computer Scientist, U.S. Geological Survey

Python · PostgreSQL/PostGIS · AWS (EC2/S3) · Apache Airflow · React · R/Shiny · ArcGIS

  • Designed full-stack systems for ingesting, processing, and serving satellite raster (COG/TIFF) and LiDAR (LAZ) datasets.
  • Built and maintained real-time ETL pipelines handling tens of millions of geospatial records.
  • Improved raster load times by over 200% as storage and throughput demands increased.
  • Built interactive software with NASA enabling climate scientists to analyze Surface Water Ocean Topography satellite data for glacial lake outburst flood prediction.
  • Developed national-scale geospatial web mapping applications using React, TypeScript, and Tailwind.
AUG 2023 — JUN 2025 UC DAVIS

Staff Research Associate, University of California, Davis

Python · R · USGS NWIS API · Git

  • Designed high-performance data retrieval pipelines for streamflow data from 10,000+ USGS gauges nationwide.
  • Built multi-million-record, quality-controlled datasets for hydrologic time-series analysis.
  • Developed and deployed an R-Shiny app for calculating nitrate pore water concentrations across the conterminous United States.

Atlas — Selected Projects

39.5°N, 119.8°W

WaterMAP

Water Monitoring Above the Planet

National-scale geospatial web application serving as a central hub for hydrologic raster, vector, and polygon datasets.

React · TypeScript · Mapbox · FastAPI · PgSTAC · TiTiler

apps.usgs.gov/watermap →
SWOT · L2

WISP

Water Information from Space

National-scale geospatial web application focused on Surface Water Ocean Topography satellite data visualizations.

React · MUI · Hydrocron API

apps.usgs.gov/wisp →
61.2°N, 147.0°W

Glacial Lake Elevations

USGS Data Release · 2nd Author

Published analysis of remotely sensed water surface elevation data for glacial lakes in Alaska, informing decisions around outburst flood risk.

Python · GeoJSON · NetCDF · NASA Earthdata API

doi.org/10.5066/p1ur7dhm →

Legend — Technical Stack

Programming

Python, R, JavaScript (React), SQL (PostgreSQL/PostGIS), Lua

Geospatial & Remote Sensing

Raster & vector analysis, COGs, STAC/PgSTAC, TiTiler, LiDAR (LAZ), NetCDF, DEMs, ArcGIS Pro

Data Engineering

ETL pipeline design, Apache Airflow, spatial databases, real-time data processing

Cloud & Deployment

AWS (EC2, S3), Linux, Git, CI/CD

Web & Visualization

React, Vite, Tailwind, Mapbox, CesiumJS, Tableau, R-Shiny

Machine Learning

Statistical modeling, time-series analysis, deep learning, foundation models

Contact

Open to geospatial, environmental, and climate-focused roles. Reach out directly.

LinkedIn GitHub