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Cloud Native Geospatial Scientist

Job in Boulder, Boulder County, Colorado, 80301, USA
Listing for: Lynker
Full Time position
Listed on 2026-08-22
Job specializations:
  • Software Development
    Data Scientist, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below

Lynker Corporation is a leading provider of innovative solutions in weather and climate science. With a commitment to excellence and a passion for innovation, Lynker leverages cutting-edge technologies and scientific expertise to support the creation and delivery of improved operational weather forecasts.

As part of our ongoing growth and expansion, we are seeking a dynamic and experienced Geospatial Scientist to join our growing team.

We work with terabytes of terrain, hydrography, and imagery, and much of the value comes from organizing it so a modeler can actually find and use it. At Lynker, we build the hydrologic and environmental data behind water models used nationwide, and we deliver it the way modern geospatial teams do as cloud-native data and live products, not static files and one-off analyses.

These two roles build that pipeline and the products that run on top of it.

We are hiring two Geospatial Scientists with strong software development skills. One role leans toward data infrastructure STAC catalogs, cloud-optimized formats (Cloud Optimized GeoTIFFs, Geo Parquet, and Zarr), and scalable processing pipelines. The other leans toward operational products turning that data into hydrologic and environmental layers, services, and regularly updated scientific products. Most of the work is in Python, and a background in hydrology or environmental science is a strong advantage.

Duties

of the Geospatial Scientist will include the following SHARED RESPONSIBILITIES
  • Software development write and maintain clean, tested Python that runs reliably over large areas.
  • Large-scale data work with large raster and vector datasets using cloud-native formats and storage.
  • Collaboration build things other teams can use, working with the Platform, Science, Modeling, and Applications teams.
EMPHASIS ONE DATA PIPELINES & CLOUD-NATIVE INFRASTRUCTURE
  • Catalogs & formats build and maintain STAC catalogs and cloud-optimized data (COG, Geo Parquet, Zarr) so large datasets are searchable and quick to access.
  • Pipelines write reproducible pipelines that process terrain, hydrography, and imagery at regional to continental scale, using distributed compute.
  • Services stand up and run the services that publish and tile the data, such as pgSTAC and TiTiler, and keep them reliable and versioned.
EMPHASIS TWO GEOSPATIAL PRODUCTS & ENVIRONMENTAL ANALYSIS
  • Products turn data into hydrologic and environmental map layers, and help move models into operational scientific products and forecasts that are regularly updated.
  • Analysis apply remote sensing and, where appropriate, machine learning to environmental and land-cover mapping.
  • Usable outputs make outputs that are clear and usable for scientists, partners, and downstream applications.
The Geospatial Scientist selected should have the following
  • Master's in geospatial science, geography, environmental or earth science, hydrology, computer science, or a related field; or a Bachelor's plus 2 years building geospatial data pipelines, tools, or cloud-native services; or equivalent hands‑on experience in place of a degree.
  • Strong Python and solid software habits Git, testing, and code review.
  • Real experience with cloud-native geospatial formats and services, and hands-on AWS experience (our primary cloud); GCP or Azure experience also welcome.
  • Solid geospatial fundamentals projections, raster and vector data, and common GIS tools.
The Ideal Geospatial Scientist will have the following
  • Experience with the STAC ecosystem and tools such as pgSTAC, stac-fastapi, or TiTiler.
  • Distributed processing with Dask, Spark, cloud batch, or Google Earth Engine.
  • The modern geospatial Python stack xarray, rasterio, geopandas, and formats like COG, Geo Parquet, and Zarr.
  • Infrastructure-as-Code and CI/CD for AWS deployments (e.g., Terraform or Cloud Formation, Docker, Git Hub Actions).
  • Turning models or analyses into operational, regularly updated products or forecasts.
  • Machine learning and remote sensing for environmental or land-cover work.
  • Background in hydrology or environmental science.
  • Colorado Front Range presence for periodic in-person collaboration.
About Lynker

Lynker is a growing, employee owned business, specializing in professional, scientific and technical services. Our continually expanding team combines scientific expertise with mature, results-driven processes and tools to achieve technically sound, cost effective solutions in hydrology/water sciences, geospatial analysis, information technology, resource management, conservation, and management and business process improvement.

We focus on putting the right people in the right place to be effective. And having the right people is critical for success. Our streamlined organization enables and empowers our talented professionals to tackle our customers' scientific and technical priorities - creatively and effectively.

Lynker offers a team-oriented work environment, and the opportunity to work in a culture of exceptionally skilled professionals who embrace sound science and…

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