Carbon Mapper is seeking a skilled Scientific Software Engineer with a passion for scientific computing and expertise in geospatial or earth science data.
Description
In this role, you will be responsible for productionizing Python science code and algorithms, transforming them into robust, production-ready solutions. You will implement these solutions within a data pipeline environment, optimizing and ensuring efficient utilization of AWS resources such as Lambda, S3, and EC2. Your strong understanding of science code and techniques, along with your software engineering skills, will be crucial for advancing our mission. You will collaborate closely with our science team to translate research prototypes into scalable and maintainable code.
Essential Duties and Responsibilities
The essential functions include, but are not limited to the following:
- Science collaboration: Partnering with the science team to produce high-quality production-ready Python code.
- Science enablement: Co-develop and maintain a data research computing environment, assisting scientists with data organization, execution, and analysis.
- Understanding Scientific Concepts: Ability to grasp the atmospheric, geospatial, and methane science the software is applied to. This involves learning specific scientific terminology, data formats, and analysis methods.
- Testing and Debugging: Writing unit tests, integration tests, and performing code reviews to ensure code quality and functionality. Debugging complex scientific algorithms and identifying errors.
- Documentation: Writing clear and concise documentation for the scientific code, including user guides, API references, and deployment instructions.
- Maintainability: Ensuring the code is well-structured, modular, and easy to understand for future maintenance and updates.
- Interface management: Integrating with the production catalog and database using STAC standards (SpatioTemporal Asset Catalogs).
- Version Control: Effectively using GitLab CI/CD or other version control systems to track code changes, collaborate with the team, and manage different code versions.
Minimum Qualifications (Knowledge, Skills, and Abilities)
- 5+ years of software engineering experience.
- Strong expertise in Python programming, particularly in scientific and data-centric computing.
- Background experience in an earth science related field.
- In-depth knowledge and experience working with geospatial or earth science data, including familiarity with geospatial specifications such as STAC and libraries such as GDAL and rasterio.
- Familiarity with AWS cloud services such as Lambda, S3, and EC2 including optimizing resource usage for efficient cloud data processing.
- Experience designing and building data pipelines including optimizing code and data workflows for performance and efficiency, especially in the context of large datasets.
- Strong understanding of software engineering principles, including version control (e.g., GitLab, GitHub), testing, code review, and continuous integration and delivery (CI/CD).
- Strong collaboration skills to work effectively with data scientists, engineers, and other team members. Clear and concise communication of technical concepts and ideas.
- Experience managing issues and epics from conception to completion, including the ability to prioritize tasks and meet deadlines.
Salary
$120,000 - $195,000 per year