Data Analyst II (Analytics) - Remote

About the Company

LanceSoft is a certified Minority Business Enterprise (MBE) and an equal opportunity employer that provides staffing and workforce solutions. The company emphasizes hiring based on qualifications, merit, and business needs while maintaining a commitment to fair employment practices and workplace inclusion.

About the Role

LanceSoft is seeking a Data Analytics professional for a 36-month remote contract focused on meteorological data analytics and science. The role involves working with large-scale weather and geospatial datasets to develop efficient analytical solutions, improve data processing, and create visualizations that support operational and business decisions.

You will collaborate with data engineers and subject matter experts to transform complex meteorological data into reliable analytical products. The ideal candidate has 3–5 years of relevant experience, strong SQL skills, and an understanding of data processing, visualization performance, and cloud-based environments.

Key Responsibilities

• Analyze and process large meteorological datasets, including numerical weather prediction outputs, satellite imagery, and weather station data.
• Develop and optimize data processing workflows to reduce processing time and memory usage.
• Create meteorological data visualizations that communicate complex information clearly to general and technical audiences.
• Troubleshoot data quality, ingestion, and pipeline issues.
• Write and maintain reusable, well-documented SQL queries and analytical datasets.
• Analyze meteorological variables from traditional numerical weather prediction and AI model outputs to identify relationships relevant to utility operations.
• Optimize the processing and visualization of large raster and geospatial datasets using techniques such as data binning, downsampling, spatial indexing, and efficient memory management.
• Collaborate with data engineers and internal subject matter experts to transition analytical products from development into operational use.
• Translate business questions into efficient analytical datasets and reliable solutions.
• Maintain data accuracy, reliability, and performance across analytical workflows.
• Prioritize tasks across multiple projects and communicate findings and technical issues clearly.

Required Qualifications

• 3–5 years of professional experience in data analytics or data science using meteorological data sources.
• Experience working with large, complex meteorological datasets in cloud-based environments.
• Demonstrated experience moving a product or analytical solution from development into operational use.
• Experience troubleshooting data quality, pipeline, and ingestion issues.
• Strong SQL skills, including joins, common table expressions (CTEs), window functions, and query performance optimization.
• Experience processing large datasets efficiently with attention to processing time and memory consumption.
• Strong understanding of how data structures affect visualization performance and usability.
• Ability to explain technical findings and data issues clearly to technical and non-technical audiences.
• Strong analytical, problem-solving, and organizational skills.
• Ability to work independently while collaborating effectively with data engineers and internal subject matter experts.
• Ability to prioritize work across multiple projects and adapt to changing needs.
• Strong attention to detail and a commitment to data accuracy and reliability.

Preferred Qualifications

• Background in Atmospheric Science, Earth Science, or a related discipline.
• Experience using Python for data analysis and transformation.
• Experience with raster and meteorological data formats such as GRIB, GeoTIFF, NetCDF, and Zarr.
• Experience working with geospatial data and optimization techniques such as spatial indexing.
• Experience developing static visualizations using Python or interactive visualizations using JavaScript.
• Knowledge of statistical concepts, including correlation, trend analysis, and least-squares fitting.
• Familiarity with multithreading and multiprocessing techniques for large-scale data processing.
• Experience with Git or similar version-control tools.
• Basic understanding of data governance, data lineage, and metadata management.
• Experience in utilities, energy, infrastructure, or other regulated industries.
• Familiarity with operational, asset, and time-series data.
• Experience working with imperfect or operational source systems.

Technical Skills

• Large-scale data processing and performance optimization.
• Meteorological and geospatial data analysis.
• SQL querying and analytical dataset development.
• Python-based data analysis and transformation.
• Data visualization and efficient handling of large raster datasets.
• Cloud-based data processing.
• Data quality troubleshooting and pipeline optimization.
• Statistical analysis and data governance concepts.

Compensation and Employment Details

• Hourly pay range of $35–$43.
• Payment structure: W-2 employment.
• Contract duration: 36 months.

Location and Work Arrangement

• Fully remote position.
• Long-term contract assignment.
• Collaboration with data engineers and internal subject matter experts is required.

Equal Employment Opportunity

LanceSoft is a certified Minority Business Enterprise (MBE) and an equal opportunity employer. The company prohibits discrimination and harassment based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other characteristic protected by applicable federal, state, or local laws. Employment decisions are based on qualifications, merit, and business needs.