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Geospatial Data Engineer Remote Jobs in Missouri

Jobgether

$88.40K - $106.10K/yr

Working in a fully remote, international environment, you'll collaborate closely with data scientists, ML engineers, and developers to ensure high-quality, reliable, and well-structured data flows.

New

nimble

Data Engineer

Chesterfield, MO · On-site +1

$113.30K - $136.10K/yr

Description Data Engineer Chesterfield Office Hybrid or Remote Why You'll Want to Join! Join a leading Revenue Cycle Management (RCM) company dedicated to transforming healthcare data into actionable ...

Nimble Solutions

Data Engineer

Wildwood, MO · On-site +1

$107.40K - $129K/yr

Data Engineer Chesterfield Office Hybrid or Remote Why You'll Want to Join! Join a leading Revenue Cycle Management (RCM) company dedicated to transforming healthcare data into actionable insights.

Nimble Solutions

Data Engineer

Chesterfield, MO · On-site +1

$113.30K - $136.10K/yr

Job Type Full-time Description Data Engineer Chesterfield Office Hybrid or Remote Why You'll Want to Join! Join a leading Revenue Cycle Management (RCM) company dedicated to transforming healthcare ...

Navtech

Sr Data Engineer

Lake Saint Louis, MO · Remote

$108.50K - $130.30K/yr

Remote till march 2022 Duration : 6 Months C2H W2 ONLY Day to Day Responsibilities of this Position and Description of Project: Senior Data Engineer Position Purpose: This position will provide the ...

Stellar IT Group

BioTech Data Engineer

Saint Louis, MO · Remote

$111.30K - $133.70K/yr

Remote The Biotech Data Engineer focuses on designing, building, and maintaining scalable Azure Databricks-based data pipelines and architectures that enable analytics, AI/ML, and reporting across ...

Koantek

Data Engineer - Multiple Positions

Chesterfield, MO · Remote

$113.30K - $136.10K/yr

United States - Remote Employment Type: Full-Time and Contract Data Engineer Description: As a Data Engineer at Koantek, you will leverage advanced data engineering techniques and analytics to ...

Jobgether

You will work in a collaborative, remote-first environment alongside engineers, analysts, and data specialists who are passionate about innovation and scalable infrastructure. The position combines ...

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Geospatial Data Engineer Remote information

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 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 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 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 Missouri? For Geospatial Data Engineer Remote jobs in Missouri, the most frequently searched job titles are:
What job categories do people searching Geospatial Data Engineer Remote jobs in Missouri look for? The top searched job categories for Geospatial Data Engineer Remote jobs in Missouri are:
What cities in Missouri are hiring for Geospatial Data Engineer Remote jobs? Cities in Missouri with the most Geospatial Data Engineer Remote job openings:
Geospatial Data Engineer Remote jobs near you
Senior Geospatial Data Engineer

Senior Geospatial Data Engineer

Object Computing, Inc.

Saint Louis, MO • On-site, Remote

$103.10K - $140K/yr

Full-time

Posted 11 days ago

Job description

Object Computing, Inc. is seeking a Senior Geospatial Data Engineer to join our Xtrack Product Team. In this role, you will lead the design and implementation of scalable, cloud-based geospatial data infrastructures, and play a key part in shaping our data architecture and product engineering strategy with a focus on improving safety and operational efficiencies for organizations in the rail industry. You will work with cutting-edge technologies in image processing, artificial intelligence, cloud computing, and geospatial database management. Your work will optimize complex business processes and unlock new value from large-scale geospatial datasets.
What you will do:
  • Architect, design, and maintain robust, scalable data pipelines and infrastructures for geospatial and big data applications maintaining a focus on performance and the ultimate end-user product experience.
  • Lead the development and optimization of ETL processes for ingesting, cleaning, transforming, and storing large volumes of geospatial and tabular data.
  • Design, build, and interact with API-driven, service-to-service web services (using FastAPI, Litestar, Flask, etc.) to enable integration across a suite of products.
  • Collaborate with backend and platform engineers to ensure secure, reliable, and scalable service-to-service communication.
  • Translate complex analytics and business questions into actionable, production-grade data solutions.
  • Collaborate closely with data scientists, analysts, and business stakeholders to deliver high-impact data products.
  • Drive the adoption and optimization of cloud-based data solutions (e.g., GCP, AWS, Azure).
  • Ensure data quality, integrity, and security across all stages of the data lifecycle.
  • Mentor and provide technical guidance to junior data engineers and team members.
  • Communicate technical details and insights clearly to both technical and non-technical audiences, including leadership.
  • Proactively recommend and implement improvements to existing data infrastructure and software programs.
  • Stay current with industry trends and emerging technologies in geospatial data engineering.

What you will bring:
  • An excitement and dedication towards manifesting real and measurable impact for customers and clients and a dedication to being a team player towards achievement of those outcomes.
  • Experience in software development, data engineering, or big data roles, preferably with a focus on geospatial data.
  • Experience building solutions with Python.
  • Experience with relational databases (e.g., SQL), including advanced query building, data extraction, and manipulation.
  • Experience architecting and optimizing cloud-based data solutions (preferably GCP, AWS, or Azure).
  • Deep experience with big data technologies such as Hadoop, Spark, MapReduce, or Kafka.
  • Experience integrating with API-driven, service-to-service web services.
  • Demonstrated ability to lead projects, mentor team members, and drive technical decisions.
  • Strong problem-solving skills, resourcefulness, and ability to work independently or collaboratively.
  • Excellent organizational, interpersonal, and communication skills.

What will make you stand out:
  • Expertise with geospatial libraries and tools (e.g., GDAL, PDAL, PostGIS, GeoPandas, Shapely).
  • Experience deploying and scaling machine learning (ML) models/algorithms in production.
  • Strong experience with geospatial analytics and working with geospatial data formats (e.g., LAS, LAZ, COPC, GeoTIFF, Shapefiles).
  • Experience leading teams in integrating and scaling complex ML/Deep Learning (DL) algorithms.
  • Experience working with LiDAR data and deriving real-world insights from point clouds.
  • Experience with ESRI products (ArcGIS Pro, ArcGIS Online, ArcGIS Enterprise) or other GIS platforms.
  • Experience with data streaming, real-time data processing, or cloud-native geospatial solutions.
  • Cloud certifications (e.g., Google Cloud Professional Data Engineer, AWS Certified Data Analytics).
  • Experience with OAuth, authentication, and API key management for secure service-to-service communication.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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