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Geospatial Data Engineer Remote Jobs in North Carolina

Sunergi Inc

$110K - $140K/yr

The Machine Learning Engineer role is all about building, recruiting, management, internal ... You are a core contributor on ML projects with a focus on data ingestion, transformation and ...

Wood Plc

Transmission Line Engineer (remote)

Raleigh, NC · On-site +1

Reporting to the Engineering Manager, South East Region. This is a remote role but would like the ... data to the client * Maintaining and enhancing relationships with internal groups and external ...

ICF

Senior Transmission Line Engineer - REMOTE

Charlotte, NC · Remote

$102K - $140K/yr

Title: Senior Transmission Line Engineer Location: Remote US Ready to make a difference? We are ... Prepare and review technical documentation such as specifications, data sheets, RFQs, bid ...

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Geospatial Data Engineer Remote information

What is a geospatial data engineer?

A Geospatial Data Engineer is a technology professional who designs, develops, and manages systems for collecting, storing, analyzing, and visualizing geospatial (location-based) data. They work with geographic information systems (GIS), spatial databases, and cloud platforms to process large datasets from sources like satellites, drones, and sensors. In a remote setting, they collaborate with teams online to build and maintain geospatial data pipelines and support decision-making for industries such as urban planning, environmental science, and logistics.

What are the typical challenges faced by remote geospatial data engineers when collaborating with distributed teams?

Remote Geospatial Data Engineers often navigate challenges such as coordinating across different time zones, ensuring data consistency, and maintaining effective communication with team members who may have varying technical backgrounds. Utilizing collaborative tools like version control systems and cloud-based platforms helps streamline workflows, but clear documentation and regular check-ins are essential to prevent misunderstandings. Building strong relationships virtually and proactively addressing technical or logistical issues can greatly enhance productivity and teamwork in a remote setting.

What are the key skills and qualifications needed to thrive as a geospatial data engineer in a remote role, and why are they important?

To thrive as a Geospatial Data Engineer (Remote), you need a strong background in GIS, geospatial analysis, and computer science, often supported by a related degree and experience with spatial databases. Proficiency with tools like Python, SQL, PostGIS, ArcGIS, and cloud platforms is typically required, along with relevant certifications such as GISP. Excellent problem-solving, communication, and self-management skills are essential for collaborating across distributed teams and delivering results independently. These skills ensure effective management of complex geospatial datasets, seamless integration of spatial data solutions, and success in a remote work environment.

What is the difference between Geospatial Data Engineer Remote vs GIS Analyst?

AspectGeospatial Data Engineer RemoteGIS Analyst
Required CredentialsBachelor's in GIS, Geography, Computer Science; experience with GIS software and programmingBachelor's in Geography, GIS, or related field; proficiency in GIS tools
Work EnvironmentRemote, often collaborative with teams across locationsTypically office-based or hybrid; fieldwork possible
Employer & Industry UsageTech companies, government agencies, environmental firmsUrban planning, government, environmental consulting
Common Search & ComparisonOften compared for GIS and data engineering roles in remote settings

The main difference between a Geospatial Data Engineer Remote and a GIS Analyst lies in their focus and skill set. Geospatial Data Engineers primarily develop and maintain data pipelines and infrastructure, often requiring programming skills, while GIS Analysts focus on spatial data analysis and map creation. Both roles may work remotely and share similar educational backgrounds, but their daily tasks and technical expertise differ significantly.

What are popular job titles related to Geospatial Data Engineer Remote jobs in North Carolina?

For Geospatial Data Engineer Remote jobs in North Carolina, the most frequently searched job titles are:

What job categories do people searching Geospatial Data Engineer Remote jobs in North Carolina look for?

The top searched job categories for Geospatial Data Engineer Remote jobs in North Carolina are:

What cities in North Carolina are hiring for Geospatial Data Engineer Remote jobs?

Cities in North Carolina with the most Geospatial Data Engineer Remote job openings:

Geospatial Data Engineer Remote jobs near you
Infographic showing various Geospatial Data Engineer Remote job openings in North Carolina as of August 2026, with employment types broken down into 71% Full Time, 10% Part Time, and 19% Contract. Highlights an 100% Remote job distribution.

Machine Learning Engineer (Remote)

Sunergi Inc

Remote

$110K - $140K/yr

Full-time

Re-posted 10 days ago

Key responsibilities

  • Implement data pipelines focused on Machine Learning applications and develop data sets for proof of concepts.

  • Partner with cross-functional teams to define, develop, and implement data technology solutions for ML applications.

  • Take ownership of individual platform components, help set the vision and architecture, and identify requirements for new features.

Job description

Sunergi Inc.Machine Learning EngineerFull-time


We are expanding rapidly and are seeking new, experienced and hands-on team members who think outside of the box (and are not afraid to share their thoughts), will deliver unique ideas and like to work in a fast-paced environment on cutting edge projects.


Our missionWe aim to map the best plots for solar panels in the United States.



The Machine Learning Engineer role is all about building, recruiting, management, internal communication and delivery - getting the product out the door, while ensuring the team is hitting their mark. Furthermore, the role will help to grow the engineering team, establish the engineering culture and remove impediments to help team members be able to provide their best.
Key Qualifications
  • You are a core contributor on ML projects with a focus on data ingestion, transformation and presentation for ML apps and reporting.
  • Passionate and dedicated track record of designing and implementing scalable, performant data pipelines, data services, and data products.
  • This is a hands-on position, expect to write more code.
  • Proficiency in at least one programming language (Java, Python or Scala) and a tried understanding of SQL.
  • Previous experience of dealing with multivariate data at petabyte scale, especially in the time-series domain.
  • Be able to communicate collaboratively with Data Scientists and ML Software developers to understand requirements we have and deliver best in class data platform.
  • Previous experience with statistical modeling and deep learning frameworks / libraries we use is required.
  • Strong aptitude for learning new technologies related to Data Management and Data Science.
  • Proven record to create and perform independently and within a fast-paced, team-oriented environment.
  • Work with structured and unstructured data. Perform data cleansing, scraping unstructured data and converting into structured data.
  • Evaluate, benchmark and improve the scalability, robustness, efficiency and performance of big data platform and applications.
  • Experience with Kubernetes, Docker is a plus
Description

In this role, handle implementing data pipelines focused on Machine Learning applications. 


  • You will develop data sets for POCs to demonstrate new insights. 
  • Several of these may lead to fully operational ML models and deploy and own the life-cycle on in-house and third party cloud environments. 
  • You will partner with various cross functional teams to define, develop and implement data technology solutions, with an emphasis on providing superior foundational data for ML applications. 
  • A strong understanding of distributed data systems and experience in using open source frameworks to build applications is required. 
  • A solid understanding of Deep learning platforms such as Keras, Tensor-flow and/or PyTorch is highly desirable, as is an ability to deploy solutions based on these platforms. 
  • Leveraging GPU & CPU resources as appropriate / understanding capacity requirements for ML Workloads, and working with partner teams to ensure scalability, business continuity and appropriate turnaround time is a key part of the operationalization effort. 
  • As a member of the team, you will be expected to take ownership of individual platform components and help set the vision and architecture for those. 
  • In the process, you will identify the requirements of new features, and propose design and drive the solution. 
  • A strong understanding of data governance and data privacy is expected for this role in keeping with Apple's strong commitment to the same.
Education & Experience

B.S or M.S in Computer Science, Mathematics, Statistics, Operational Research, Data Science / equivalent experience.

Additional Requirements
  • 3+ years of proven experience with Kubernetes, Docker is a plus

Compensation

  • 0.25% company equity, with vesting options up to 2%.
  • A strong, competitive salary upon reaching a seed round of funding. In the range of $110k-$140k/ year.



Employment Type: FULL_TIME

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