Biodiversity Data Engineer

Job Description
1. Develop data architectures and workflows to analyze spatial biodiversity data at a global scale. 2. Efficiently organize and query data in multiple database systems 3. Develop repeatable analytical workflows using high-performance computing clusters and cloud platforms. 4. Maintain and improve connections with various data repositories. 5. Create and maintain organized documentation. 6. Effectively collaborate with a diverse team and external partners. 7. Efficiently communicate analytical processes to audiences of varying expertise. 

Required Education and Experience
Master’s Degree in computer science, applied/computational mathematics, biostatistics, statistics, informatics, ecology, environmental science, or a related field and two years of demonstrated experience or an equivalent combination of education and demonstrated experience.

Background Check Requirements
All candidates for employment will be subject to pre-employment background screening for this position, which may include motor vehicle, DOT certification, drug testing and credit checks based on the position description and job requirements. All offers are contingent upon the successful completion of the background check. For additional information on the background check requirements and process visit "Learn about background checks" under the Applicant Support Resources section of Careers on the It's Your Yale website.

Position Focus:
The Biodiversity Data Engineer will join a team of researchers and informaticians at the Center for Biodiversity and Global Change at Yale University (bgc.yale.edu) to design and implement large spatial biodiversity analytical workflows and databases. They will build and maintain cloud computational infrastructure to efficiently produce global biodiversity datasets to inform conservation decision-making and policy. They will work closely with large data repositories (e.g., GBIF, eBIRD, FishBase, Wildlife Insights, etc.) and co-develop private data systems with partners. The candidate will be responsible for maintaining rigorous data standards and scientific integrity. 

The Center for Biodiversity and Global Change at Yale University is home to Map of Life (MOL.org), which supports effective global biodiversity education, monitoring, research, and decision-making by assembling and integrating a wide range of knowledge about species distributions and their dynamics over time. Our team also leads the data integration and mapping efforts of the Half-Earth Project to identify and prioritize target areas for global biodiversity conservation. We work to support decision-making to conserve biodiversity using the best available science. 

The Biodiversity Data Engineer will build and maintain data systems and datasets to support existing partnerships spanning many sectors (e.g., national governments, international and local conservation NGOs, business, finance, academia, etc.). We are proud of our long-term relationships, for example with NASA, Esri, Google, the E.O. Wilson Biodiversity Foundation, the GEO Biodiversity Observation Network, and the Field Museum who have facilitated numerous local and regional engagements. 

We strongly encourage members of underrepresented groups in the sciences to apply. Historical and ongoing social inequities rooted in racism, sexism, ableism, and other forms of discrimination result in the continued and widespread exclusion of marginalized groups from academic spaces. At our Center, we strive to support individuals from diverse backgrounds and to create a safe and inclusive community to counter these legacies of discrimination within the ecological and environmental sciences. We are actively committed to building a team and community where individuals representing a variety of paths to the sciences are brought together to foster a community of learning and collaboration. We hope that our commitments and actions create a more supportive and inspiring environment for individuals and contribute to a more inclusive and equitable future for our field.
 
Yale University offers a thriving and growing international community of scholars, including efforts such as the Peabody Museum and the School of the Environment. Yale University is located two hours from New York City and Boston, with several public transportation options.

Preferred Education, Experience and Skills:
Ph.D. may be beneficial but is not required.

Posting Disclaimer
The intent of this job description is to provide a representative summary of the essential functions that will be required of the position and should not be construed as a declaration of specific duties and responsibilities of the particular position. Employees will be assigned specific job-related duties through their hiring departments.

University policy is committed to affirmative action under law in employment of women, minority group members, individuals with disabilities, and protected veterans. Additionally, in accordance with Yale’s Policy Against Discrimination and Harassment, and as delineated by federal and Connecticut law, Yale does not discriminate in admissions, educational programs, or employment against any individual on account of that individual’s sex, sexual orientation, gender identity or expression, race, color, national or ethnic origin, religion, age, disability, status as a special disabled veteran, veteran of the Vietnam era or other covered veteran.

Inquiries concerning Yale’s Policy Against Discrimination and Harassment may be referred to the Office of Institutional Equity and Accessibility (OIEA).

Required Skill/Ability 1:
Expertise in database management for spatial data (PostgreSQL and PostGIS).

Required Skill/Ability 2:
Proficiency in analyzing large biodiversity datasets in platforms such as Google Earth Engine, BigQuery, or other cloud computing environments.

Required Skill/Ability 3:
Proficiency in data preparation and management of biodiversity data (e.g., traits, taxonomies, occurrences).

Required Skill/Ability 4:
Demonstrated experience with global scale remotely-sensed imagery data, environment, and climate products.

Required Skill/Ability 5:
Demonstrated experience in spatial statistical analysis in R, Python, or ArcGIS.