[Hiring] Data Analytics Analyst @4P Consulting

Role Description

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
• Large dataset performance optimization

Qualifications

• 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.

Requirements

• 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.

Key Skills

• 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