Data Analytics Analyst

We are seeking a Data Analytics Analyst with experience working with large-scale meteorological and geospatial datasets to support analytics, visualization, and operational decision-making.

This role will focus on processing and analyzing weather data from sources such as numerical weather prediction models, satellite imagery, and weather stations. The ideal candidate will have strong experience with Python, SQL, cloud-based data environments, data visualization, geospatial data, and large dataset performance optimization.

• Analyze large and complex meteorological datasets in cloud-based environments.

• Process numerical weather prediction, satellite, weather station, and related data sources.

• Optimize data processing to reduce runtime and memory usage.

• Develop reusable and well-documented SQL queries using joins, CTEs, and window functions.

• Create clear meteorological data visualizations for technical and non-technical audiences.

• Develop static visualizations using Python and/or interactive visualizations using JavaScript.

• Troubleshoot data quality, ingestion, and pipeline issues.

• Support products from development through operational deployment.

• Identify meteorological variables that may correlate with utility operations.

• Work with large raster and geospatial datasets.

• Improve visualization performance through techniques such as downsampling, binning, and efficient data structures.

• Collaborate with data engineers and internal subject matter experts.

• Translate business questions into efficient analytical datasets.

• Maintain strong data accuracy, reliability, and documentation.

• 3 5 years of professional experience in data analytics or data science using meteorological data.

• Experience working with large, complex datasets in a cloud environment.

• Experience guiding analytical or data products from development into operations.

• Strong troubleshooting experience with data quality, pipeline, or ingestion issues.

• Strong SQL skills, including:

  • Joins

  • CTEs

  • Window functions

  • Query optimization

• Understanding of meteorological variables and numerical weather prediction outputs.

• Strong knowledge of data visualization and large-dataset performance considerations.

• Strong analytical and problem-solving skills.

• Excellent written and verbal communication skills.

• Ability to work independently while collaborating with technical teams and SMEs.

• Background in Atmospheric Science, Meteorology, Earth Science, or a related discipline.

• Strong Python experience for data analysis and transformations.

• Experience with raster data formats such as:

  • GRIB

  • GeoTIFF

  • NetCDF

  • Zarr

• Experience with geospatial data and spatial indexing.

• Knowledge of statistical methods, including correlation and trend analysis.

• Familiarity with multithreading or multiprocessing for large-scale data processing.

• Experience with Git or similar version-control tools.

• Understanding of data governance, lineage, and metadata management.

• Utility, energy, infrastructure, or regulated-industry experience.

• Experience with operational, asset, or time-series data.

Data Analytics | Meteorological Data | Weather Data | Python | SQL | Geospatial Data | Numerical Weather Prediction | NWP | GRIB | GeoTIFF | NetCDF | Zarr | Raster Data | Data Visualization | Cloud Analytics | Time-Series Data | Data Quality | Data Pipelines | Git | Statistical Analysis