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Meteorological Data Analyst Meteorological Data Analyst Contractual Birmingham, AL Job ID:

OOJ - 22056

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Back to search results Meteorological Data Analyst 3-5 years of professional experience in data analytics or data science leveraging meteorological data sources (e.g., numerical weather prediction output, satellite imagery, weather station data) Proven experience working with large, complex meteorological datasets in a cloud-based environment Demonstrated experience guiding a product from development to operations Demonstrated experience troubleshooting data quality, pipeline, or ingestion issues Technical Skills & Languages Processing data at scale Ability to optimize processing of meteorological data to consume minimal time and memory Familiarity with cloud-optimized formats for raster data like Zarr Creating meteorological data visualizations Ability to package meteorological output in a way that is understandable to a general audience Familiarity with static visualizations using Python and/or interactive visualizations using JavaScript SQL Familiarity with joins, CTEs, window functions, performance optimization Writing and maintaining reusable, well-documented queries Analytics & Visualization Strong understanding of how data structure impacts visualization performance and usability Familiarity with common bottlenecks when rendering large datasets and their resolution (e.g., data binning, downsampling, efficient plotting methods and memory use) Understanding of meteorological variables in traditional numerical weather prediction and AI model output and the ability to identify those that may be correlated with utility operations Soft Skills & Work Style Strong analytical and problem-solving skills Ability to work independently while collaborating with data engineers and internal SMEs Clear written and verbal communication, especially when explaining data issues or findings Experience prioritizing work across multiple projects Preferred Qualifications Background in Atmospheric Science or another Earth Science Technical Preferences Experience with Python for data analysis and transformations Experience working with raster datasets in formats like GRIB, GeoTIFF, and NetCDF Experience with geospatial data and performance optimizations when working with geospatial data such as leveraging spatial indices Knowledge of basic statistical concepts like correlation and trend analysis using methods like least-squares fitting Familiarity with the concepts of using multiple threads and/or multiple CPUs to process large datasets quickly Experience with version control (Git or similar) Basic understanding of data governance, lineage, or metadata management Domain & Business Experience Experience in utilities, energy, infrastructure, or regulated industries Familiarity with operational, asset, or time-series data Experience working with imperfect or operational source systems Professional Attributes Ability to translate business questions into efficient analytical datasets Demonstrated attention to detail with a strong focus on data accuracy and reliability APPLY NOW