Senior Geospatial Software Engineer

We are seeking a skilled Geospatial Software Engineer to advance Gro’s data storage and processing for our expanding geospatial datasets. This includes high resolution and multi-dimensional climate, environmental, and satellite data that are used to drive Gro’s product offerings and predictive models. The ideal candidate will have a strong background in building, optimizing, and maintaining systems that store and operate on large amounts of data in various geospatial formats.

What You'll Do

• Design, implement, and maintain high throughput data pipelines that allow scientists to quickly analyze and transform large geospatial (multi-dimensional, high resolution) datasets in the cloud
• Manage, optimize, and even redesign existing geospatial data workflows and storage systems
• Design, implement, and manage data storage solutions for large geospatial datasets
• Collaborate with scientists, analysts, researchers, and software developers to deliver high-quality geospatial data products and services
• Work with cross-functional teams to integrate geospatial data processing tasks

Who you are

• Someone who loves to learn, is willing to experiment, and remains adaptable
• Understands geospatial data and computational challenges for N-dimensional array data and GIS data
• Someone who is passionate about building and optimizing distributed parallel computing systems and crunching loads of data quickly and efficiently
• Self-motivated to drive projects to completion
• Open-minded about languages/tools/frameworks, and able to make good decisions about which to use (and when) to solve a particular problem
• A great team player; someone with a point of view who knows how to humbly express it

What we're looking for

• Ability to create and clearly communicate designs and ideas
• 6 years of experience in geospatial software engineering, including cloud data pipelines, big data architecture, and automation
• Expertise in Python
• Experience with GIS libraries (e.g. GDAL, Rasterio, Rioxarray, Shapely, GeoPandas)
• Fluency with cloud (AWS, GCP, or Azure) infrastructure (AWS preferred)
• Experience with geospatial data formats and schemas - both legacy (HDF, NetCDF, GRIB) and cloud-optimized (GeoTIFF, TileDB, Zarr)
• Fluency with one or more cloud-based distributed computing frameworks (e.g. Dask, Spark)
• Experience with workflow management tools (e.g. Airflow, Dagster)
• BS in Computer Science, a related technical field, or equivalent practical experience
• Experience with cloud-native software development using containers (e.g. Kubernetes, ECS)

Nice to Have

• Experience with collaborative platforms (e.g. GitHub, GitLab)
• Experience with object stores (S3, Azure Blob Storage, etc)
• Knowledge of data science,machine learning, and statistical models
• Experience with Geospatial or highly pixelated data sets
• Experience in technical leadership, leading project teams, and setting technical direction
• Proficiency with or willingness to learn Rust

Compensation

The salary range for this role is expected to be $130,000 - $225,000. Other compensation for the role includes equity, a generous PTO policy and health, vision & dental insurance.