Backend & Data Engineer

AccelOne LLC; United States; Remote; USD 110,000 - 165,000; Full time

Benefits offered by this job

Remote work

Job summary

AccelOne LLC is seeking a Backend & Data Engineer (GIS/Geospatial Imagery) to join our data team. This remote, full-time role emphasizes Python, backend engineering, and handling large geospatial datasets.

Ideal candidates will bring strong GIS experience, photogrammetry or image processing know-how, and hands-on AWS expertise to build scalable data pipelines and processing workflows.

Qualifications

• 5+ years in backend or data engineering.
• Strong Python proficiency.
• Hands-on GIS/geospatial data experience.
• Experience with geospatial imagery processing.
• Experience building or maintaining scalable data pipelines.

Responsibilities

• Develop, maintain, and support backend and data processing systems using Python.
• Work daily with core processing systems and large-scale geospatial imagery.
• Build and maintain reliable data processing workflows and pipelines.
• Process, transform, and manage geospatial data and imagery.
• Apply GIS knowledge to support geospatial data processing and analysis.
• Collaborate with engineering and data teams to improve processing solutions.
• Troubleshoot data-processing and backend issues and improve system reliability.
• Support scalability and performance of systems handling large data volumes.
• Contribute to continuous improvement of engineering and data-processing practices.

Skills

Python

Backend Eng

Data Eng

GIS data

Photogrammetry

AWS

Job description

Backend & Data Engineer — GIS / Geospatial Imagery

Remote | Full-time

About the Project

Our client is a U.S.-based technology company working with large-scale geospatial data and imagery.

We are looking for an experienced Backend & Data Engineer to join their data team, with an expected start as soon as possible.

This role will work closely with the team’s core processing systems and large-scale geospatial imagery, combining backend engineering and data processing with hands-on experience in GIS and photogrammetry and/or image processing.

The ideal candidate has strong Python skills, solid backend and data engineering experience, and practical experience working with geospatial data and imagery. Strong AWS experience is a significant plus.

Responsibilities

• Develop, maintain, and support backend and data processing systems using Python.
• Work daily with core processing systems and large-scale geospatial imagery.
• Build and maintain reliable data processing workflows and pipelines.
• Process, transform, and manage geospatial data and imagery.
• Apply hands-on GIS knowledge to support geospatial data processing and analysis.
• Work with photogrammetry and/or image-processing workflows.
• Collaborate with engineering and data team members to develop and improve processing solutions.
• Troubleshoot data-processing and backend issues and contribute to system reliability.
• Support the scalability and performance of systems handling large volumes of geospatial data.
• Contribute to the continued improvement of engineering and data-processing practices.

Requirements

• Strong professional experience in backend engineering and/or data engineering.
• Strong proficiency in Python.
• Hands-on professional experience with GIS and geospatial data.
• Experience with photogrammetry and/or image processing.
• Experience working with geospatial imagery.
• Experience developing or maintaining data-processing systems or pipelines.
• Ability to work with large-scale datasets and processing workflows.
• Strong analytical and problem-solving skills.
• Ability to work effectively within a collaborative engineering environment.
• Availability to join the project as soon as possible.

Nice to Have

• Strong hands-on experience with AWS.
• Experience building or supporting cloud-based data-processing systems.
• Experience working with large-scale geospatial imagery processing.
• Experience optimizing data pipelines or processing systems for performance and scalability.
• Previous experience working with distributed engineering teams.