Data Engineer (Climate & Water Resources)

Data Engineer (Climate & Water Resources)

Position Overview

We are seeking a highly skilled Data Engineer with experience in climate-related and water resources data management. The ideal candidate will develop, optimize, and maintain data pipelines for hydrological, meteorological, and climate datasets. This role involves working with large geospatial and time-series data, supporting climate risk assessments, flood modeling, and water resource management projects.

Key Responsibilities:

• Automate data collection from sources such as NOAA, ECMWF, IMD, NASA, and regional hydrological agencies.
• Process and clean large datasets, ensuring data integrity, accuracy, and accessibility.
• Handle large-scale geospatial and time-series datasets related to rainfall, river discharge, groundwater levels, and climate models.
• Work with climate projection datasets (e.g., CMIP6, ERA5) for impact assessments and forecasting.
• Develop efficient storage solutions using cloud platforms (AWS, GCP, or Azure).
• Support hydrological and hydraulic modeling teams by structuring input data for flood simulations, drought analysis, and climate impact assessments.
• Collaborate with data scientists to build machine learning models for climate risk assessment.
• Implement scalable data processing workflows using Python, SQL, and distributed computing tools.
• Optimize data workflows for efficient processing and visualization.
• Work closely with hydrologists, climate scientists, and engineers to understand data requirements.
• Document data pipelines, metadata, and workflows for reproducibility and transparency.

Required Qualifications & Skills:

Education & Experience

• Bachelors or Masters degree in Computer Science, Data Science, Environmental Engineering, Hydrology, Climate Science, or a related field.
• 3-5 Years of experience in data engineering, preferably in climate science, hydrology, or environmental domains.

Technical Skills

• Strong programming skills in Python, SQL, or R.
• Experience with big data processing tools (Apache Spark, Dask, or Hadoop).
• Familiarity with climate and hydrological datasets (HECRAS, HEC HMS, SWAT, GFS).
• Experience with geospatial data tools (GDAL, PostGIS, GeoPandas).
• Knowledge of cloud platforms (AWS S3, GCP BigQuery, Azure Data Lake).

Preferred Skills

• Experience in climate risk modeling and statistical analysis of environmental data.
• Familiarity with APIs for climate data access (Copernicus, NASA Earthdata).
• Understanding of hydrological models and remote sensing datasets.