Data Engineer at Axiom Data Science

What we do

Axiom is a fast-moving and dynamic ~20-person technology and informatics firm with a mission to build a better understanding of society and the environment by increasing the accessibility, reuse, and impact of scientific data. To that end, we provide cyberinfrastructure support, data management systems, and scalable technical solutions for organizing and analyzing large amounts of diverse datasets to organizations across the globe. We’ve assembled an outstanding team of software and data engineers, data analysts, project managers, and data coordinators to tackle difficult problems and provide excellent support to our partners at businesses, non-profits, federal and state agencies, and universities. This is an exciting time for Axiom, and we are looking forward to taking on new team members as we grow.

We offer a flexible, collaborative working environment, and we have a company culture that promotes taking initiative, solving problems, and maintaining a healthy work-life balance. We want to do great work, while being a great place to work. We are headquartered in Anchorage, AK and have satellite offices in Portland, OR; North Kingstown, RI; Washington, DC; Homer, AK; and Fairbanks, AK. Work location for this position is flexible and may be remote, though we would prefer someone in close proximity to one of our offices. Approximately ⅓ of Axiom currently works remotely.

How we work

We are a software-services company forming mutually beneficial partnerships with partners. We believe in focusing time and energy on our core products, and encouraging staff to take ownership of their work.

We are a geographically distributed company and collaborate with each other online. Strong communication skills are critical. We work together closely while minimizing distractions.

We have low administrative overhead. Staff are given all the tools they need to excel and are self-driven, resourceful, and instrumental in expanding our vision.

What you’ll do

The Axiom team works to enhance and sustain scientific data by upscaling metadata, semantically linking datasets, developing specialized services, creating powerful visualizations, and applying advanced analysis techniques.
 

As a data engineer you will contribute to and advance our suite of scientific data management tools, techniques, and services. This is not a research position, the work you do has the opportunity to directly impact the organization and our users everyday. There are occasional research opportunities at Axiom that data engineers lead or take part in but it is not the primary role of a Data Engineer at Axiom. Example tasks that Data Engineers at Axiom are involved with on a daily basis are:

• Develop routines for extracting, transforming, manipulating, formatting, compiling, and curating large and complex geo-physical and scientific data types primarily in the coastal and ocean domains;
• Develop and contribute to existing data services built to deal with large-scale scientific datasets;
• Contribute to translating scientific data and analytic results into end-user products;
• Prototype analysis code in Jupyter and migrate a production-ready version of the code into a data processing pipeline.

What we look for

Data science exists at the intersection of three domains: computer science, mathematics and statistics, and scientific expertise. We are seeking a candidate who can contribute to each of these domains through prior experience handling and analyzing marine, atmospheric or geospatial data. Experience with community standard open-source tools and scientific data formats is important, but inspiration, vision, motivation, determination, and commitment are the qualities Axiom values most. As a small company taking on complex information science challenges, Axiom depends on all employees being multi-talented, imaginative, and resourceful. Staff are provided with the tools they need to perform at their highest level and rewarded with an employee-focused work environment.
 

We are looking for a demonstrated history of working with real-world data, and that you have some of the following skills and experiences:

• 4+ years of relevant experience with a spectrum of environmental scientific data formats;
• Degree in computer science, statistics, mathematics, or similar quantitative discipline; or a degree in the physical and/or environmental sciences with quantitative and programming experience;
• Experience working in a collaborative team environment;
• Experience working within a Linux environment or the willingness to learn;
• Experience with the core concepts of software engineering (e.g. source control, continuous integration tools, unit testing and coding best practices);
• Experience with the core Python data science stack;
• Experience building and working with services and APIs on top of large scientific and/or geospatial datasets;
• Experience with core GIS concepts such as rasters, vectors, projections and spatial operations;
• Experience with geospatial databases and storage formats (e.g., GeoTIFF, ESRI Shapefile/geodatabase, NetCDF, PostgreSQL/PostGIS, GeoJSON, etc.);
• Willingness to dive in and embrace other aspects of our technology stack: Docker, Ansible, Git, Jupyter, Apache Spark, GeoServer, Dask, TimescaleDB, Parquet/Arrow, Node, React, D3.js
• Self-motivation, independence, flexibility, and a problem-solving attitude

What you’ll get
Competitive salary between $70k and $120k commensurate with experience. Benefits include 5 weeks paid leave plus holidays, healthcare reimbursement, a company-matching 401K plan, and a gym membership.

How to apply

If you are interested in this position, please apply through https://axiomdatascience.com/jobs/. Your resume and/or cover letter should describe how your experiences fit with the desired qualifications of the position and what drove you to apply for the position. Please include links to projects you have worked on and explanation of your role; web links to relevant personal websites and/or projects; and examples of any open source participation (e.g., GitHub, StackOverflow), as available.