Geospatial Data Analyst - Python

DenkenSolutions Inc is seeking a Geospatial Data Analyst with Python expertise to join our Birmingham, Alabama team in a hybrid onsite/remote arrangement. The role centers on Python-based geospatial data processing, analytics, and dashboards, handling large, cloud-based datasets and addressing data quality issues. The position offers an hourly rate around USD 56 and requires a minimum of three years of relevant experience.

Responsibilities

• Experience with geospatial data processing in Python
• Experience supporting enterprise reporting, dashboards, and analytics products
• Demonstrated experience troubleshooting data quality, pipeline, or ingestion issues

Requirements

• 3-5 years of professional experience in data analytics, business intelligence, or a related role
• Proven experience working with large, complex datasets in a cloud-based environment
• Experience with geospatial data processing in Python
• 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 data requests and investigations

Technologies

• Python
• GDAL
• rasterio
• geopandas
• Databricks
• Azure Synapse
• Snowflake
• BigQuery
• Power BI
• Tableau
• PySpark
• Git
• GeoTIFF
• ETL/ELT pipelines
• Spatial indices

Technical Skills & Languages

• Data Modeling & Transformation
• Ability to prepare data optimized for analysis, visualization, and dashboard consumption
• Ability to write robust code that handles edge cases, implements retries, and fails gracefully under error conditions

SQL

• Familiarity with joins, CTEs, window functions, and performance optimization
• Writing and maintaining reusable, well-documented queries

Cloud Data Platforms

• Hands-on experience with Databricks, Azure Synapse, Snowflake, BigQuery, or similar platforms
• Understanding of how data moves from source systems into cloud storage and analytics layers

Data Quality & Validation

• Ability to identify discrepancies between source systems and cloud datasets
• Experience facilitating root-cause analysis and coordinating resolution across teams

Analytics & Visualization

• Strong understanding of how data structure impacts visualization performance and usability
• Familiarity with bottlenecks when rendering large datasets and their resolution (data binning, downsampling, efficient plotting methods, and memory use)
• Experience using plotting libraries in Python to create charts and graphs
• Experience supporting dashboards and reports using tools such as Power BI, Tableau, or similar enterprise BI platforms

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 data requests and investigations

Preferred Qualifications

• Background in Atmospheric Science or another Earth Science
• Experience with data visualization (Power BI) is a plus

Technical Preferences

• Experience with PySpark or Python for data analysis and transformations
• Experience working with GeoTIFFs or other raster datasets
• Experience with geospatial data and performance optimizations, such as leveraging spatial indices
• Knowledge of basic statistical concepts like correlation and trend analysis using methods like least-squares fitting
• Familiarity with using multiple threads and/or multiple CPUs to process large datasets quickly
• Familiarity with ETL / ELT pipelines and orchestration concepts
• Experience with version control (Git or similar)
• Basic understanding of data governance, lineage, or metadata management

Professional Attributes

• Ability to translate business questions into efficient analytical datasets
• Demonstrated attention to detail with a strong focus on data accuracy and reliability