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Geoscience Software Engineer Jobs in Salt Lake City, UT

DGI Geoscience Inc.

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Geology Technician

Salt Lake City, UT · On-site

$26 - $30/hr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

DGI Geoscience is looking for Geological Technician to join our team! DGI is a leader in ... engineering, and resource development projects. We are committed to scientific excellence, safety ...

Zanskar

Senior Distributed Systems Engineer

Salt Lake City, UT · Hybrid

$101K - $138K/yr

To reduce risk and improve outcomes, we rely on novel software and machine learning modeling. Who ... geoscience concepts and applications. Location and Benefits * The position is based out of our ...

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All JobsGeoscience Software Engineer JobsGeoscience Software Engineer Jobs in Salt Lake City, UT

Geoscience Software Engineer information

See Salt Lake City, UT salary details

$61.5K

$142.8K

$198.9K

How much do geoscience software engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for geoscience software engineer in Salt Lake City, UT is $142,760.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,100.00 and $167,400.00 per year, depending on experience, location, and employer.

What is a geoscience software engineer?

A Geoscience Software Engineer is a professional who develops, maintains, and optimizes software applications used in the geosciences, such as geology, geophysics, and environmental science. They work closely with geoscientists and data analysts to create tools that help interpret and visualize subsurface data, model geological processes, and support exploration or environmental projects. This role typically requires strong programming skills, knowledge of geoscience concepts, and experience with specialized software or data formats used in the field.

What are some common challenges geoscience software engineers face when integrating geological data into software solutions?

Geoscience Software Engineers often encounter challenges related to the complexity and variety of geological data formats, as well as the need to accurately model subsurface structures. Translating real-world geoscience concepts into computational algorithms requires close collaboration with geologists and domain experts to ensure accuracy. Additionally, maintaining performance and scalability when processing large datasets can be demanding, especially when working with real-time or high-resolution data. These challenges make cross-disciplinary communication and continuous learning essential in this role.

What are the key skills and qualifications needed to thrive as a geoscience software engineer, and why are they important?

To thrive as a Geoscience Software Engineer, you need a strong background in computer science, geology or geophysics, and experience with programming languages such as Python, C++, or Java. Familiarity with industry-specific tools like Petrel, ArcGIS, and seismic interpretation software, as well as version control systems (e.g., Git), is typically expected, along with relevant certifications or advanced degrees. Strong problem-solving skills, teamwork, and effective communication are crucial for collaborating with multidisciplinary teams and translating complex geoscientific data into reliable software solutions. These skills ensure the development of robust, user-friendly applications that support critical decision-making in energy, environmental, and research sectors.

What is the difference between Geoscience Software Engineer vs Geoscientist?

AspectGeoscience Software EngineerGeoscientist
Required CredentialsBachelor's or Master's in Geoscience, Computer Science, or related fieldBachelor's or higher in Geoscience or Earth Sciences
Work EnvironmentDevelops software tools for geoscience applications, often in tech or research firmsConducts fieldwork, data analysis, and research in labs or on-site
Industry UsageUsed in tech companies, oil & gas, environmental consultingUsed in academia, research institutions, and environmental agencies

While Geoscience Software Engineers focus on developing software solutions for geoscience problems, Geoscientists primarily conduct fieldwork and research to understand Earth's processes. Both roles require a strong foundation in geoscience, but their daily tasks and work environments differ significantly.

What are popular job titles related to Geoscience Software Engineer jobs in Salt Lake City, UT?

For Geoscience Software Engineer jobs in Salt Lake City, UT, the most frequently searched job titles are:

What job categories do people searching Geoscience Software Engineer jobs in Salt Lake City, UT look for?

The top searched job categories for Geoscience Software Engineer jobs in Salt Lake City, UT are:

What cities near Salt Lake City, UT are hiring for Geoscience Software Engineer jobs?

Cities near Salt Lake City, UT with the most Geoscience Software Engineer job openings:

Geoscience Software Engineer jobs near you

Full-Stack Software Engineer, Platform Data

Jobtailor

Salt Lake City, UT • On-site

$120 - $180/hr

Other

Posted yesterday

New

Job description

  • Design and operate pipelines that ingest data from many sources - internal systems, purchased datasets, and external feeds - reconciling them into clean, well-modeled, findable data that people trust.
  • Build the web apps which deliver that data to stakeholders including dashboards, internal applications, and other interfaces.
  • Own features end to end: designing system architecture, pipelines, APIs, and frontends, while being accountable for ensuring the entire system runs smoothly.
  • Partner directly with teams across the organization to understand what they're trying to learn from the data, then build the thing that allows them to answer their questions.
Requirements
  • Full-stack builder: You've built and maintained backend data systems and their associated user-facing applications. You're fluent in Python and SQL on the backend and in TypeScript and React on the frontend. You own features spanning the whole path from source to screen.
  • Data engineering instincts: You've designed schemas and built pipelines that move data reliably from messy sources into clean, queryable form. You think about idempotency, data quality, and what happens when an upstream source changes. Experience with orchestration and warehouse tooling (e.g., Airflow, Dagster, dbt, Snowflake, or BigQuery) is a strong plus. Experience with geospatial or scientific data - raster/vector formats, large file stores, PostGIS, or similar - is also nice-to-have.
  • Product-minded and collaborative: You can sit with a geoscientist, watch where they get stuck, and translate that into shipped products. You treat stakeholders as partners, working comfortably across teams, keeping people in the loop, surfacing trade-offs early, and building alignment on what to build and why.
  • Cloud & infrastructure fluency: You're comfortable deploying and operating what you build on a public cloud (AWS or GCP), with containers (Kubernetes) and infrastructure-as-code (e.g., Pulumi and Terraform).
  • Self-directed and comfortable with unsolved problems: You research options and make recommendations, doing your best work when the problem is real and the constraints are hard. You leverage and delegate to AI, treating modern AI tools as a core part of how you work, handing off tasks to AI agents to use them as a force-multiplier.
Core Competencies

Demonstrates expertise in full-stack development, including backend data systems and user-facing applications, with a strong focus on data engineering, cloud infrastructure, and collaboration with stakeholders to deliver impactful solutions.

Highest-signal resume keywords
  • Python Programming
  • SQL Database Management
  • TypeScript Development
  • React Framework
  • Data Pipeline Design
ATS Optimization Keywords Hard Skills
  • Data Engineering
  • Schema Design
  • API Development
  • Frontend Development
  • Backend Development
  • Data Quality Assurance
  • Orchestration Tools
  • Cloud Deployment
  • Infrastructure as Code
  • Geospatial Data Handling
Soft Skills
  • Collaborative Problem Solving
  • Stakeholder Engagement
  • Self-Direction
  • Communication
  • Product Mindset
Industry Keywords
  • Data Ingestion
  • Data Modeling
  • Data Quality
  • Idempotency
  • Public Cloud
  • Containers
  • AI Tools
  • Geoscience
  • Raster Data
  • Vector Data
Tools & Technologies
  • AWS
  • GCP
  • Kubernetes
  • Airflow
  • Dagster
  • Dbt
  • Snowflake
  • BigQuery
  • Pulumi
  • Terraform
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