Remote Data Engineer Government Jobs in Kansas (NOW HIRING)

As a Solutions Engineer at Overstory, you'll turn our vegetation intelligence into operational impact for utility customers. Our data products - derived from satellite imagery and machine learning - give utilities a clearer picture of where vegetation poses risk to their power lines. Vegetation-caused outages are a leading cause of power disruption and a growing driver of wildfire risk, and climate change is making the problem harder. You'll deliver analyses with technical and geospatial depth, build tools and workflows that make our work scale, and help customers actually act on what we provide. You'll use geospatial analysis, Python, and Overstory's data products to solve real utility problems today, and help shape what becomes a scalable product capability tomorrow.

This role is a great fit for someone who loves working with large geospatial datasets and wants to grow into customer advisory, product, or operational work at a high-growth mission-driven company. Highlights:

• Ownership: Innovate on, deliver, and grow a critical capability for a fast-growing business - from customer delivery through scalable productization.
• Impact: Make a tangible, scalable contribution to climate resilience in the power sector.
• Skills: Use your geospatial and technical toolkit while building product judgment, customer-facing depth, startup operating experience, and your craft with AI tools.
• Trajectory: Grow your career at a high-growth company, staying in Solutions Engineering or with pathways into Product, Customer Success, Sales, or Strategy.

Time Zone Requirement: North America (EST preferred)

On a typical day, you might be: running satellite imagery through a pipeline and validating the output; debugging a geospatial join in Python; reviewing a draft analysis with a Customer Success Manager before it goes to a customer; talking with a utility vegetation manager to walk through findings and adjust based on what you hear; refactoring a notebook into a reusable script for the team; or sketching out how a recurring customer ask could become a product feature.

• Own customer projects end-to-end, from data requests and processing through analysis to customer-ready outputs, in close partnership with Customer Success.
• Work with large geospatial datasets (vector and raster) from Overstory's platform, customers, and third-party sources - process, validate, analyze, and turn them into outputs customers can act on.
• Build rapport with customer counterparts. Translate technical findings into recommendations that change decisions and lead to better outcomes for our customers.

• Identify patterns across customer work that are worth standardizing and productizing. Convert one-off projects into repeatable artifacts.
• Strengthen engineering quality so analytical work is easier to validate, hand off, and scale.
• Partner with product and engineering to build the productization roadmap.
• Strengthen the analytics workflows and infrastructure that support both customer impact and future productization.

• Passionate about tackling climate challenges with data-driven solutions.
• 2-4 years of professional experience working with large, complex geospatial datasets in a customer- or stakeholder-facing capacity.
• Proficiency with a Python-driven analytical and engineering stack - Python, Jupyter, git/GitHub, and command-line workflows.
• Experience successfully managing multiple projects simultaneously.
• Demonstrated attention to detail and care with data.
• Demonstrable experience (or at a minimum a serious interest in) leveraging AI tooling to amplify your work.
• Proven ability to solve ambiguous problems and collaborate effectively with stakeholders.
• Excellent communication, including translating technical findings for non-technical audiences and building rapport with customer counterparts.

• Background in utility operations, infrastructure, or vegetation management
• Experience with remote sensing, satellite imagery, or other earth observation data
• SQL or experience with data engineering pipelines
• Prior work in a high-growth startup or mission-driven company