Wildlife Health Lab Data Engineer

The Cornell University College of Veterinary Medicine seeks a Data Engineer to join the Wildlife Health Lab (CWHL) team. The selected person will work in collaboration with application developers, data scientists, ecologists, and wildlife professionals using data pipelines that integrate raw wildlife agency data into data systems. The Data Engineer will further prepare data for and run large analytical processes written in R, Python, or other languages. The Data Engineer will migrate current local processes to cloud services, as well as write and maintain system documentation. The Data Engineer will support development goals by publishing and maintaining data resources systems for wildlife agencies. 

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, Statistics, or other relevant technical data-centric computational field and 3-5 years of relevant experience or equivalent combination

• Familiarity with wildlife disease ecology, wildlife management, environmental science, natural resource management, or other related fields. 

• Knowledge of the development and maintenance of databases, data storage, processing, and APIs.

• Experience with relational and No SQL database software (such as Postgres, MySQL, and MongoDB), containerization software (such as Docker), cloud computing services (such as Google Cloud, Microsoft Azure, and AWS), and web application frameworks (such as R Shiny).

• Experience building reliable data pipelines that ingest and process data at scale. 

• Knowledge of data security, including the appropriate handling of sensitive data and the maintenance of data privacy throughout all computations and workflows. 

• Experience publishing in scientific literature.

• Outstanding communication, collaboration, time management, and task management skills. 

• Exceptional independent multi-tasking ability with accountability and follow-through.

• Must be able to manage multiple projects simultaneously, as well as adhere to deadlines associated with each task.

• Must be able to work independently and to work successfully in a team-oriented environment.

Preferred Qualifications

• Master’s degree or higher in Computer Science, Data Science, Statistics, or other relevant technical data-centric computational field.

• Interdisciplinary training or experience in applied quantitative settings to conduct science in ecology, natural resources, or epidemiology.

• Experience with web application development, user interface design, and web development.

• Experience working with or for governmental wildlife agencies. 

• Dedication to a career supporting the fields of wildlife, natural resources management, or conservation.

Important Details about the Position

• This is a hybrid position located in Ithaca, NY with the expectation of 1 day onsite per week.

• This is a full time one-year term position with potential for extension contingent upon performance and funding.

• We are unable to provide Visa sponsorship, now or in the future, for this position.

• Relocation assistance will not be provided for this position.

While the regular business hours are 8:00 am to 5:00 pm, the specific schedule may change to meet the needs of the business, requiring employees to work early mornings, evenings, weekends and University holidays and scheduled breaks.

The Following Documents are Required to be Submitted with your Application

• Resume

• Cover Letter

What We Offer:

Great benefits! Cornell receives national recognition as an award-winning workplace for our health, wellbeing, and sustainability.

• 3 weeks of paid vacation

• 13 additional holiday days with generous holiday pay if you work on those days

• An award-winning employer provided benefits program

  • Comprehensive health care options

  • Access to wellness programs

  • Employee discounts with local and national retail brands

  • Generous retirement contributions

  • Impressive educational benefits include tuition-free Extramural Study and Employee Degree Program, Tuition Aid for external educatio