Hydrology Engineer – Water Resources & Flood Modeling
Safeguard communities and ecosystems as a Hydrology Engineer specializing in data-driven watershed modeling, flood flow forecasting, and drought resilience.
Key Responsibilities
- Analyze multi-decade rainfall and streamflow records, cleansing and validating raw data for statistical soundness.
- Delineate complex watersheds and quantify runoff using HEC-HMS, TR-55/20, and custom Python scripts.
- Build, calibrate, and stress-test hydrologic models that predict surface- and ground-water interaction under changing climate scenarios.
- Prepare floodplain maps, support FEMA submittals, and inform stormwater infrastructure design.
- Assess regional water-supply yield, drought probability, and aquifer recharge; translate findings into actionable engineering reports.
- Present concise technical briefings to public agencies, mining operators, and private developers.
- Mentor junior analysts in GIS best practices and reproducible data pipelines.
- Collaborate remotely with cross-disciplinary civil, structural, and environmental teams.
Qualifications
- Bachelor’s or higher in Civil Engineering, Hydrology, Water Resources, Environmental Engineering, or related field.
- 4+ years hands-on experience as a Hydrology Engineer, Hydrologist, or Water Resources Engineer.
- Proven mastery of HEC-HMS and ArcGIS; familiarity with TR-55/20, SWMM, or GSSHA desirable.
- Proficient in Python or R for statistical hydrologic analysis, data loggers, and automated QA/QC workflows.
- Deep understanding of surface-water dynamics, groundwater principles, and climate-driven variability.
- Strong command of probability, frequency analysis, and stochastic modeling.
- Exceptional written and verbal communication; able to distill technical results for non-engineers.
- FE/EIT required; PE license or plan to obtain within 24 months preferred.
- Eligibility to work in the United States; ability to travel up to 10 % for site reconnaissance.
Tools & Tech Stack
- HEC-HMS, HEC-RAS (1D/2D), TR-55/20.
- ArcGIS Pro, QGIS, GeoHMS, Raster/Vector geoprocessing.
- Python (Pandas, NumPy, SciPy), R (tidyverse), Jupyter.
- PostgreSQL/PostGIS, Git version control, cloud-based data storage.
- NOAA, USGS, and NRCS hydrologic databases.