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Geospatial Data Engineer Remote Jobs in Texas (NOW HIRING)

Scalepex

AWS Data Engineer - Fully Remote - US Only

Plano, TX · Remote

$109K - $131K/yr

About the Role We are seeking an experienced AWS Data Engineer with a strong background in building scalable data solutions and expertise in utilities-related datasets. The ideal candidate will have ...

Siena AI

Run demos built around the prospect's actual problems and data, across our Support, Shopping ... Be the connective tissue across Sales, Engineering, Product, and CS: triage issues, file well ...

Cisco

Senior Software Engineer (Remote)

Austin, TX · Remote

$121K - $160K/yr

This is a remote role anywhere in the USA. Meet the Team Our software engineering team develops ... Work with data technologies such as PostgreSQL, MySQL, and Redis to support reliable, scalable ...

Cisco

Senior Software Engineer (Remote)

Houston, TX · Remote

$117K - $154K/yr

This is a remote role anywhere in the USA. Meet the Team Our software engineering team develops ... Work with data technologies such as PostgreSQL, MySQL, and Redis to support reliable, scalable ...

Cisco

Senior Software Engineer (Remote)

Dallas, TX · Remote

$121K - $159K/yr

This is a remote role anywhere in the USA. Meet the Team Our software engineering team develops ... Work with data technologies such as PostgreSQL, MySQL, and Redis to support reliable, scalable ...

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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 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 Remote jobs in Texas?

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

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

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

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

Cities in Texas 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 Texas as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

AWS Data Engineer - Fully Remote - US Only

Scalepex

Plano, TX • Remote

$109K - $131K/yr

Full-time

Re-posted 4 days ago

Job description

Why Scalepex?

Scalepex is a dynamic services firm specializing in providing solutions for premium brands like Nike, Pepsi, Toyota, Virgin and Walgreens. Our mission is to connect prominent market leaders with top-tier professionals from around the world, fostering collaboration, efficiency, and growth.

Take your portfolio to the next level by working with one of our fastest growing clients.

Join the Innovation Frontier at Scalepex!

About the Role

We are seeking an experienced AWS Data Engineer with a strong background in building scalable data solutions and expertise in utilities-related datasets. The ideal candidate will have at least 5 years of experience in data engineering, a deep understanding of distributed systems, and proficiency with AWS services and tools like Step Functions, Lambda, Glue, and Redshift. This role will focus on designing, developing, and optimizing data pipelines to support analytics and decision-making in the utilities industry.

Key Responsibilities

  • Design and Build Data Pipelines: Develop scalable, reliable data pipelines using AWS services (e.g., Glue, S3, Redshift) to process and transform large datasets from utility systems like smart meters or energy grids.
  • Workflow Orchestration: Use AWS Step Functions to orchestrate workflows across data pipelines; experience with Airflow is acceptable but Step Functions is preferred.
  • Data Integration and Transformation: Implement ETL/ELT processes using PySpark, Python, and Pandas to clean, transform, and integrate data from multiple sources into unified datasets.
  • Distributed Systems Expertise: Leverage experience with complex distributed systems to ensure reliability, scalability, and performance in handling large-scale utility data.
  • Serverless Application Development: Use AWS Lambda functions to build serverless solutions for automating data processing tasks.
  • Data Modeling for Analytics: Design data models tailored for utilities use cases (e.g., energy consumption forecasting) to enable advanced analytics
  • Optimize Data Pipelines: Continuously monitor and improve the performance of data pipelines to reduce latency, enhance throughput, and ensure high availability.
  • Ensure Data Security and Compliance: Implement robust security measures to protect sensitive utility data and ensure compliance with industry regulations.

Requirements

Required Qualifications

  • Minimum of 5 years of experience in data engineering
  • Proficiency in AWS services such as Step Functions, Lambda, Glue, S3, DynamoDB, and Redshift.
  • Strong programming skills in Python with experience using PySpark and Pandas for large-scale data processing.
  • Hands-on experience with distributed systems and scalable architectures.
  • Knowledge of ETL/ELT processes for integrating diverse datasets into centralized systems.
  • Familiarity with utilities-specific datasets (e.g., smart meters, energy grids) is highly desirable.
  • Strong analytical skills with the ability to work on unstructured datasets.
  • Knowledge of data governance practices to ensure accuracy, consistency, and security of data.
  • Strong experience in AWS data engineering
  • Ability to work independently
  • Ability to work with a cross-functional teams, including interfacing and communicating with business stakeholders
  • Professional oral and written communication skills
  • Strong problem solving and troubleshooting skills with experience exercising mature judgement
  • Excellent teamwork and interpersonal skills
  • Ability to obtain and maintain the required clearance for this role

Apply