Geospatial Data Engineer - Government (Secret)

Geospatial Data Engineer - Government (Secret)

This job is no longer open
The Company
Descartes Labs is a cutting edge company currently ranked #40 in the world for high performance compute (HPC) and top three (3) in the United States. This distinction validates that Descartes Labs is the leading provider of peta-scale geospatial analytics. The Descartes Labs Government business is applying the same state-of-the-art applications that rank us in the top categories nationally and internationally to help Government, Public Sector and Military organizations with big geospatial data challenges achieve mission success. Our cloud platform enables rapid ingestion and normalization of petascale, geospatially enabled data and facilitates the ability to rapidly train, test, and deploy AI/ML solutions that optimize manual analytical workflows. More specifically, the Descartes Labs platform assists our customers to corral their multi-sensor, multi-intelligence ecosystems by applying scientific analysis to cross-functional challenges at a regional and global level thereby creating new sources of insights and operational advantage for government and warfighter end users to rapidly make informed decisions.

The Role
Descartes Labs is looking for a geospatial data engineer with strong experience building data-processing pipelines and familiarity with earth observation data. This role will help us build our cloud-based supercomputer that currently ingests 10 Terabytes of near real-time geospatial data per day.  Our microservices-based platform is developed from the ground up cloud-native, and we see a peak load of nearly 1 billion API calls a day. We aim to supercharge machine learning scientists to ask geospatial and temporal questions not previously possible by building a world-class catalog of analysis ready data.

Minimum Salary: $120,000 USD

Your Impact

    • Deliver a wide range of datasets, from raster to vector, multispectral to radar, to the DL platform.
    • Expand our geospatial data offerings through harmonization and normalisation transformations.
    • Make our data storage and access faster and more scalable.
    • Work with our data science team to build a system that allows clients to focus on analysis and problem solving.
    • Contribute your own ideas to the larger engineering and data science teams.

What You Bring

    • 2-3 years of experience in data engineering .
    • Strong familiarity with Linux systems.
    • Real-world software experience in Python is required; experience in other languages is also valuable.
    • Experience with geospatial, planetary, or astronomical datasets is required.
    • Demonstrated experience with established geospatial libraries (gdal, pyproj, shapely, pdal, etc).
    • Proficiency with git and modern distributed version control system practices is required.
    • Code examples (preferably github / bitbucket / etc) are required.
    • Familiarity with cloud systems (AWS / Google Cloud / Azure) and cloud infrastructure is a plus.
    • Familiarity with Kubernetes and distributed computing is a plus.

Who You Are

    • Curious. You are always exploring and experimenting, interested in why and how, seeking not only to understand but to make work and the world better. You enthusiastically share your learning with others and actively seek information and knowledge. 
    • Conscientious. You are determined, always keep your promises, and are forward thinking. Principled and integrous, you take your commitments seriously.
    • Humble. Unpretentious and self-aware, you cultivate compassion for others and take responsibility for your mistakes. Egoes are barriers to doing the best work and always learning. 
    • Open and Inclusive. You are receptive and interested in new ideas and perspectives, even when those perspectives don’t agree with your views. You value and respect difference and create ways for all people to contribute to the organization. 
    • Collaborative. You know it takes a team to get anything accomplished and you actively and inclusively work across the organization. You listen intently and openly and are always focused first on creating the best results. 
    • Adaptable. You are able to navigate changing circumstances and environments with ease and approach uncertainty with enthusiasm, while inspiring others towards effective goal setting and accomplishment.

Top Reasons to Work at Descartes Labs

    • We pride collaboration over ownership, iteration over perfection, principles over rules, and discussion over directives
    • We’re using the world’s top technology to solve the world’s largest problems with a strong focus on sustainability, environment, and impact science
    • We look at Descartes Labs as a work environment where people are included, treat their colleagues with professional regard and respect, and thrive as a result
    • We’re a highly collaborative company that constantly promotes success through teamwork
    • We strongly encourage and enjoy a flexible work environment
    • Descartes Labs offers a generous compensation package including competitive salary; choice of medical plan; dental, life, and disability insurance; paid holidays and paid time off
In response to Executive Order 14042 and accompanying Task Force Guidance, all Descartes Labs Government Inc. employees must be fully vaccinated for COVID-19 by January 18, 2022, unless a medical or religious accommodation is formally approved by Descartes Labs Government Inc. prior to employment or as otherwise required by law. Proof of vaccination is a condition of employment.

You belong here! If your experience and interests match with some of the above, we want you to apply. 

We are dedicated to building a diverse community, where employees belong, even if they are different. Scientific discovery is in our DNA, and diversity fuels innovation. 

Accommodations will be provided as requested by candidates taking part in all aspects of the selection process
This job is no longer open
Logos/outerjoin logo full

Outer Join is the premier job board for remote jobs in data science, analytics, and engineering.