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Geospatial Data Engineer Jobs in Texas (NOW HIRING)

Trinity Logistics Group

GenAI Engineer

Dallas, TX

Process and optimize large-scale datasets, including IoT, telematics, and geospatial data, to support analytical and operational use cases * Establish and enforce engineering hygiene around AI work ...

TrinityRail

GenAI Engineer

Dallas, TX · On-site

Process and optimize large-scale datasets, including IoT, telematics, and geospatial data, to support analytical and operational use cases * Establish and enforce engineering hygiene around AI work ...

Trinity Industries

GenAI Engineer

Dallas, TX · On-site

Process and optimize large-scale datasets, including IoT, telematics, and geospatial data, to support analytical and operational use cases * Establish and enforce engineering hygiene around AI work ...

BAE Systems

Cartographer II

San Antonio, TX · On-site

$61K - $104K/yr

Manage a geospatial database. Perform QA/QC functions and correct data call errors. Compile ... engineering, system administration, or software configuration of industry standard geospatial ...

Pape-Dawson Engineers

GIS Technician

San Antonio, TX · On-site

... data management. * Ability to create clear, accurate maps and other geospatial deliverables. * Basic understanding of programming concepts and technical documentation. * Strong attention to detail ...

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Geospatial Data Engineer information

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How much do geospatial data engineer jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for geospatial data engineer in Texas is $43.44, according to ZipRecruiter salary data. Most workers in this role earn between $33.37 and $53.75 per hour, depending on experience, location, and employer.

What are some common challenges faced by Geospatial Data Engineers on the job?

Geospatial Data Engineers frequently encounter challenges related to integrating large and diverse spatial datasets from multiple sources, ensuring data quality, and optimizing data for efficient querying and analysis. Managing changing project requirements and staying updated with evolving geospatial technologies are also common aspects of the role. In addition, collaborating with data scientists, analysts, and GIS specialists requires clear communication to translate technical data into actionable outputs. Navigating these challenges effectively helps engineers deliver robust geospatial solutions that support business and research goals.

What are the key skills and qualifications needed to thrive in the Geospatial Data Engineer position, and why are they important?

To thrive as a Geospatial Data Engineer, you need solid expertise in geospatial data processing, spatial databases, GIS concepts, and programming languages like Python or SQL, typically backed by a relevant degree in geoinformatics, computer science, or a related field. Familiarity with tools such as ArcGIS, QGIS, PostGIS, and cloud platforms, as well as certifications like GISP, are highly valued. Strong analytical thinking, attention to detail, and collaborative communication enhance performance in multidisciplinary teams. These skills are vital for accurately transforming complex spatial data into actionable insights and delivering reliable solutions in geospatial projects.

What is a Geospatial Data Engineer job?

A Geospatial Data Engineer is responsible for designing, developing, and managing systems that process and analyze spatial data. They work with geographic information systems (GIS), databases, and cloud platforms to handle large-scale geospatial datasets. Their role involves data pipeline development, spatial analysis, and optimizing geospatial data storage and retrieval. They collaborate with analysts, scientists, and developers to support location-based decision-making.

What are the most commonly searched types of Geospatial Data Engineer jobs in Texas? The most popular types of Geospatial Data Engineer jobs in Texas are:
What are popular job titles related to Geospatial Data Engineer jobs in Texas? For Geospatial Data Engineer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Geospatial Data Engineer jobs in Texas look for? The top searched job categories for Geospatial Data Engineer jobs in Texas are:
What cities in Texas are hiring for Geospatial Data Engineer jobs? Cities in Texas with the most Geospatial Data Engineer job openings:
Geospatial Data Engineer jobs near you
Infographic showing various Geospatial Data Engineer job openings in Texas as of July 2026, with employment types broken down into 100% Full Time. Highlights an 77% In-person, and 23% Remote job distribution, with an average salary of $90,361 per year, or $43.4 per hour.

GenAI Engineer

Trinity Logistics Group

Dallas, TX

Other

Posted 29 days ago

Job description

Trinity Industries is searching for an GenAI Engineer to join our Service Analytics  organization, supporting rail optimization and shipper decisioning solutions. In this role, you will use Claude and modern AI tooling to build data pipelines, accelerate data science work, and ship production AI capabilities on top of our Azure and Databricks platform.

You will sit at the intersection of data engineering and data science. You will be involved in building data pipelines, training and evaluating models, and building LLM-powered systems - but what amplifies this role beyond a standard DS/DE seat is your fluency with Claude as a development partner: Claude Code, custom Skills, sub-agents, hooks, and the Model Context Protocol (MCP). You will partner with data engineers, data scientists, analysts, and business stakeholders to turn telematics, maintenance, and operations data into decisions our customers and operators can act on.

Join our team today and be a part of Delivering Goods for the Good of All!

What you'll do:

  • Design, develop, and operate data pipelines on Databricks ( PySpark, SQL, Python)
  • Build and ship LLM applications and agents using the Claude API - document extraction, RAG over maintenance and tariff data, internal copilots, and workflow automation
  • Use Claude Code as a primary engineering tool: author and maintain Claude Code Skills (packaged slash-command workflows), sub-agents, hooks, and MCP integrations that let the team build pipelines and analytical assets faster
  • Partner with data scientists on model development - feature pipelines, evaluation harnesses, training runs, and the path from notebook to production

  • Process and optimize large-scale datasets, including IoT, telematics, and geospatial data, to support analytical and operational use cases

  • Establish and enforce engineering hygiene around AI work - prompt evaluation, cost governance (prompt caching, model routing), monitoring, and drift detection
  • Translate ambiguous business problems from rail, service, and operations stakeholders into shipped pipelines, models, or AI tools
  • Apply version control and collaborative development practices across Azure DevOps repos and pipelines to ensure code quality and deployment readiness
  • Identify and implement process improvements and automation to improve pipeline efficiency, reliability, and maintainability
  • Partner with management to prioritize data initiatives and align engineering solutions with organizational information needs
     

What you'll need:

The core test for this role is simple: can you manage pipelines and extract data from Databricks, and can you use Claude as a real engineering partner? If yes, you can do this job.

  • Bachelor's Degree Computer Science, Information Management, or related field required; Masters preferred
  • 8+ years in data engineering including prior experience in data transformation
  • Databricks: hands-on experience building, running, and debugging data pipelines using medallion architecture (bronze / silver / gold). Comfortable extracting data, writing PySpark, SQL, and Python, and managing jobs end to end
  • IDE fluency: daily driver in VS Code, Cursor, JetBrains, or equivalent - comfortable in repos, terminals, and modern dev workflows
  • Claude Code: hands-on experience with the Claude Code architecture - Skills, sub-agents, hooks, MCP servers, and settings - and how to compose them into reliable engineering workflows. Bring examples of what you have built
  • Claude API (or equivalent): production experience with prompt design, tool use, structured output, and evaluation 
  • Applied data science: comfortable with the model lifecycle - feature engineering, evaluation, and the path from notebook to production (You do not need to be a research scientist)
  • Team engineering hygiene: Git, code review, CI, and Azure DevOps repos and pipelines
  • Communication: able to explain a model, a pipeline, or a trade-off to a non-technical stakeholder without losing them

THE FOLLOWING MUST ATTACHED TO YOUR APPLICATION:

Submit your resume along with a link to a personal GitHub repository (or public gist) showcasing your Claude Code architecture - Skills, sub-agents, hooks, MCP servers, settings, or any combination you have built. A short README explaining what each piece does and why you built it is more valuable than volume. If the repo is private, a redacted tree, settings.json, and one or two example Skill files are sufficient.

Candidates who include a working Claude Code repo with their application will be prioritized for the technical round.

Apply