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Geospatial Data Engineer Remote Jobs in Georgia (NOW HIRING)

Senior AI Engineer (Remote)

Atlanta, GA · On-site +1

$99K - $136K/yr

Operating at the intersection of Data Science, Machine Learning Engineering, and Software Engineering, this hands-on role translates AI concepts into enterprise-ready products. This role involves ...

Java Software Engineer - Remote

Atlanta, GA · On-site +1

$49.75 - $68.25/hr

... data loss prevention to all connections via the cloud, instantaneously and at scale. This ... As a Software Engineer at iboss, you'll have the opportunity to work on multiple technologies. Our ...

Data Platform Engineer

Atlanta, GA · On-site +1

$145K - $175K/yr

As a Data Platform Engineer, you will contribute to building the modern Data platform at Prizepicks ... S. and are willing to consider remote candidates. #LI-Remote Working at PrizePicks: The typical ...

Java Software Engineer - Remote

Atlanta, GA · Remote

$49.75 - $68.25/hr

... data loss prevention to all connections via the cloud, instantaneously and at scale. This ... As a Software Engineer at iboss, you'll have the opportunity to work on multiple technologies. Our ...

See us at Position Summary As a Lead Systems Engineer - Data at Bravo17, you will elevate data ... Remote; however we are looking to grow our presence in Atlanta, Chicago, Denver, and Washington DC ...

Fully Remote Position: This role is 100% remote, allowing you to work from the comfort of your home ... Partner with data engineers and BI developers to fix defects, expand monitoring, and keep ...

New

Fully Remote Position: This role is 100% remote, allowing you to work from the comfort of your home ... Partner with data engineers and BI developers to fix defects, expand monitoring, and keep ...

New

The solutions we create apply exciting technologies such as geospatial visualization and analytics ... Government Contract Mandates and access to sensitive public safety data. * Experience with ...

Showing results 41-60

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 the most commonly searched types of Geospatial Data Engineer jobs in Georgia?

The most popular types of Geospatial Data Engineer jobs in Georgia are:

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

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

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

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

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

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

Infographic showing various Geospatial Data Engineer Remote job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 11% Part Time, 7% Contract, and 3% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Senior AI Engineer (Remote)

Home Depot

Atlanta, GA • On-site, Remote

$99K - $136K/yr

Full-time

Medical, Retirement, PTO

Posted 14 days ago


Home Depot rating

7.4

Company rating: 7.4 out of 10

Based on 6,441 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

With a career at The Home Depot, you can be yourself and also be part of something bigger.
Position Purpose:
The Senior AI Engineer is responsible for designing, building, scaling, and optimizing production-grade Agentic AI systems that drive measurable business outcomes across The Home Depot. Operating at the intersection of Data Science, Machine Learning Engineering, and Software Engineering, this hands-on role translates AI concepts into enterprise-ready products.
This role involves developing scalable applications powered by LLMs, SLMs, Retrieval-Augmented Generation (RAG) frameworks, and autonomous agents. You will build the core orchestration layers for multi-agent workflows, tool integration, and planning, alongside the infrastructure required for reliable, large-scale cloud deployment. By partnering with product, engineering, and business teams, you will rapidly prototype solutions, navigate ambiguity, and seamlessly transition cutting-edge AI capabilities from concept to production.
Required skills
  • Experience: 6+ years of experience in AI, Machine Learning Engineering, or Software Engineering with strong Python development skills and modern software engineering practices.
  • AI Delivery: Proven experience building and deploying production-grade AI solutions using LLMs, SLMs, RAG frameworks, copilots, agents, and multi-agent systems.
  • AI Foundations: Deep understanding of AI/ML foundations, including transformers, embeddings, deep learning, prompt engineering, agentic reasoning patterns, and vector databases.
  • Orchestration & Integration: Experience developing orchestration layers (task execution, routing, planning, workflows) and seamlessly integrating AI solutions with enterprise platforms, APIs, and business systems.
  • Infrastructure & MLOps: Expertise in cloud-native architectures, containerization (Docker) and orchestration (Kubernetes/GKE), infrastructure as code (e.g., Terraform), andAI pipeline design, with hands-on implementation of MLOps/LLMOps best practices (CI/CD, automated testing, model versioning and registries, governance, compliance, and security) across the full AI/agent lifecycle.
  • AIOps & Deployment Reliability: Experience building automated CI/CD pipelines for AI/agentic systems, implementing progressive rollout strategies (canary, blue-green, and shadow deployments) with automated rollback, and establishing end-to-end observability (logging, metrics, distributed tracing, and automated alerting) across models, agents, and orchestration layers to ensure production reliability, performance, and cost/token efficiency at scale.
  • Optimization & Debugging: Demonstrated ability to optimize complex AI systems for performance, reliability, scalability, latency, cost efficiency, and token use, as well as debugging operational failure modes.
  • Execution & Collaboration: Excellent cross-functional communication and collaboration skills, with a proven ability to take AI solutions from concept to production in complex enterprise environments.

Key Responsibilities:
  • 70% Delivery and Execution - Collaborates and pairs with other product team members (UX, engineering, and product management) to create secure, reliable, scalable machine learning solutions; Documents, reviews, and ensures that all quality and change control standards are met; Works with Product Team to ensure user stories that are developer-ready, easy to understand, and testable; Writes custom code or scripts to automate infrastructure, monitoring services, and test cases; Writes custom code or scripts to do "destructive testing" to ensure adequate resiliency in production; Configures commercial off the shelf solutions to align with evolving business needs; Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively
  • 10% Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizations
  • 20% Support and Enablement - Fields questions from other product teams or support teams; Monitors tools and participates in conversations to encourage collaboration across product teams; Provides application support for software running in production; Proactively monitors production Service Level Objectives for products; Proactively reviews the Performance and Capacity of all aspects of production: code, infrastructure, data, message processing, and prediction quality

Direct Manager/Direct Reports:
  • This Position typically reports to Software Engineer Manager or Sr. Software Engineer Manager
  • This Position has 0 Direct Reports

Travel Requirements:
  • Typically requires overnight travel 5% to 20% of the time.

Physical Requirements:
  • Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Working Conditions:
  • Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications:
  • Must be eighteen years of age or older.
  • Must be legally permitted to work in the United States.

Preferred Qualifications:
  • Tools & Frameworks: Hands-on experience with Vertex AI, Gemini, Google ADK, LangGraph, CrewAI, AutoGen, or similar orchestration tools and frameworks.
  • AI Infrastructure & Platform Tooling: Hands-on experience with infrastructure-as-code (e.g., Terraform), Kubernetes/GKE for container orchestration, GPU/accelerator provisioning and autoscaling, model registries, feature stores, and vector database operations at production scale.
  • Full-stack skills: Node.js/React/REST, API design, performance optimization, Linux, Git, modern deployment toolchain.
  • Industry Context: Background in retail, supply chain, manufacturing, eCommerce, logistics, or finance where Applied ML is mature.
  • Guardrails & Reliability: Knowledge and experience in establishing Responsible AI, evaluation frameworks, reliability engineering, and AI governance guardrails.
  • Leadership & Innovation: A proven track record of driving innovation, delivering measurable business impact, mentoring engineering teams, and establishing AI engineering standards and best practices.
  • Master's or bachelor's in computer science, Artificial Intelligence, Machine Learning, or a related technical discipline.

Minimum Education:
  • The knowledge, skills and abilities typically acquired through the completion of a high school diploma and/or GED.

Preferred Education:
  • No additional education

Minimum Years of Work Experience:
  • 2

Preferred Years of Work Experience:
  • No additional years of experience

Minimum Leadership Experience:
  • None

Preferred Leadership Experience:
  • None

Certifications:
  • None

Competencies:
  • Global Perspective
  • Manages Ambiguity
  • Nimble Learning
  • Self-Development
  • Collaborates
  • Cultivates Innovation
  • Situational Adaptability
  • Communicates Effectively
  • Drives Results
  • Interpersonal Savvy

Benefits offered include health care benefits, 401K, ESPP, paid time off, and success sharing bonus. For a full list of the various benefits The Home Depot offers, visit https://careers.homedepot.com/our-benefits.
For California, Colorado, Connecticut, Rhode Island, Nevada, New York City, Ithaca (NY), Westchester County (NY), and Washington residents:
The pay range for this position is between $100,000.00 - $250,000.00

What Home Depot employees say

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About Home Depot

Sourced by ZipRecruiter

The Home Depot is the world’s largest home improvement specialty retailer, operating a vast network of warehouse-format stores across the United States, Canada, and Mexico. Founded in 1978, the company has established itself as the primary resource for building materials, lawn and garden products, and home décor. Its business model caters to two distinct customer bases: Do-It-Yourself (DIY) homeowners and "Pro" customers, such as professional contractors and tradespeople. Beyond product sales, the company offers an extensive suite of services, including professional installation and one of the largest tool rental operations in North America.

Industry

Retail, manufacturing and personal services

Company size

10,000+ Employees

Headquarters location

Atlanta, GA, US

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