Senior Software Engineer, DataLab

Job Summary:
As a Senior Software Engineer, you will be responsible for providing day-to-day engineering as well as technical leadership and vision for the shared backend infrastructure that powers WRI’s many impactful data platforms, such as Resource Watch, Global Forest Watch, Global Forest Watch Pro, and Aqueduct.

In this position, you will work collaboratively across a matrixed team of product managers, GIS analysts, and both in-house and external software engineers. You will work with our tech stack which includes AWS, Terraform, Docker, Github, Kubernetes, Apache Spark, PostgreSQL, and Linux. The primary language you will use is Python, but also maintain codebases in Node.js and Scala.

This position is remote due to Covid-19, but you can be based in WRI’s offices in London, the Hague, Brazil, Mexico City, or Washington, D.C., once restrictions are lifted. This position can be considered for long-term remote work for US-based candidates.

Job Responsibilities:
Data engineering & system architecture

• Oversee the full lifecycle from development to production of backend services shared across WRI’s public-facing data platforms
• Design and implement scalable, automated data processing solutions and data pipelines for integrating, updating and analyzing spatiotemporal data
• Implement intuitive and robust APIs that serve diverse clients
• Manage WRI’s AWS cloud infrastructure, including administration and security
• Produce comprehensive and easy-to-understand architecture documentation for new and existing backend components
• Keep abreast of the latest developments in relevant technologies, including geospatial processing, APIs, and AWS, and recommend new approaches where appropriate

Day-to-day engineering

• Write high-quality, readable, well-documented code using various languages (including Python, JavaScript/Node.js, Scala, SQL) and geospatial libraries (such as PostGIS, GDAL, and GeoTrellis)
• Write comprehensive unit and end-to-end tests
• Diagnose and mitigate performance issues
• Review and improve peers’ code, including mentoring junior engineers in software engineering and code quality best practices

Job Qualifications:

• Minimum of 7 years full-time work experience
• Master’s degree in relevant field, or relevant work experience in lieu of degrees
• Minimum of 3 years of leadership experience
• Experience architecting and building cloud-based software
• Experience with open source geospatial processing software, such as PostGIS, GDAL, and GeoTrellis
• Experience with designing REST APIs
• Experience with using infrastructure-as-code (Terraform preferred) and building automated CI/CD pipelines
• Passion for learning and staying on top of the new technologies, architectures, and best practices
• High proficiency in English language
• Willingness to work during US Eastern Time core office hours (approximately 9 AM - 5 PM Eastern with flexibility)

Preferred

• Experience working with and overseeing technology projects with external vendors
• Experience with Docker and Kubernetes
• Familiarity with AWS preferred

Potential Salary:
$115,000 - $156,000 if based in United States. Salary is commensurate with experience and other compensable factors.

How to Apply:
Please submit a resume with cover letter. Resume and cover letter must be submitted in English to be considered. Applicants must apply through the WRI Careers portal to be considered. 

Program Overview:
The Data Lab team works across WRI’s programs, centers and international offices to help harness the full power of the data revolution and use modern technology to solve today’s most pressing sustainability issues. The Data Lab also upholds WRI’s rigorous data standards and commitment to open data and knowledge-sharing. Global Forest Watch To stop deforestation, we need to know where it is happening and who is responsible in time to take action. Global Forest Watch (GFW) is the only free online platform providing near-real time information and analysis about when, where and why forests are changing around the world. GFW uses machine learning algorithms and expert analysis to distill satellite imagery, crowdsourced information, and hundreds of open datasets into actionable insights and policy-relevant information about forests worldwide. GFW’s online platform is simple to use, allowing anyone with an internet connection to access data, create dynamic maps, and produce custom analyses with just a few clicks. Designed for action, GFW enables researchers, government officials, companies, civil society organizations, and concerned citizens anywhere to make better-informed decisions about managing and conserving forests.