Data Analytics Analyst 2 4P/899

4P Consulting Inc.; Birmingham (AL); Remote; USD 90,000 - 130,000; Full time

Job summary

Southern Company Services is seeking a Data Analytics Analyst to work with large meteorological and geospatial datasets. You will analyze weather data from NWP models, satellites, and weather stations, and develop scalable SQL queries and visualizations for decision-making.

Ideal candidates bring Python, SQL, cloud experience, data visualization skills, and a strong background in atmospheric science or related fields, with the ability to translate business questions into analytical datasets.

Qualifications

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

Responsibilities

• 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.

Skills

Python

SQL

Data Visualization

Geospatial Data

Cloud Analytics

Time-Series Analysis

Git

Analytical Skills

Education

Atmospheric Science background

Meteorology

Earth Science

Tools

GRIB

GeoTIFF

NetCDF

Zarr

GIS

Job description

Title: Data Analytics Analyst – Meteorological Data
Client: Southern Company Services
Location: Remote
Contract: 3 Years
Experience: 3–5 Years

Job Summary

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.

Key Responsibilities

• 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.

Required 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.

Preferred Qualifications

• 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