Staff - Non Union

Job Category M&P - AAPS

Job Profile AAPS Salaried - Information Systems and Technology, Level B

Job Title Research Data Manager

Department Research | Dao Duc | Department of Mathematics | Faculty of Science

Compensation Range $6,251.00 - $8,986.00 CAD Monthly

The Compensation Range is the span between the minimum and maximum base salary for a position. The midpoint of the range is approximately halfway between the minimum and the maximum and represents an employee that possesses full job knowledge, qualifications and experience for the position. In the normal course, employees will be hired, transferred or promoted between the minimum and midpoint of the salary range for a job.

Posting End Date April 16, 2026

Note: Applications will be accepted until 11:59 PM on the Posting End Date.

Job End Date January 31, 2031

This is a grant funded term position at 60% FTE.

At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and creates the necessary conditions for a rewarding career.

Job Summary

Working in a dynamic and high-energy environment, the Data Manager will assist and support Wittman/Dao Duc Research Groups, including collaborating researchers, with duties associated with designing, building, and maintaining data systems and decision-support tools for sustainable, climate-resilient food systems research. The incumbent will lead the development of a bilingual decision-support dashboard, maintain the project’s data infrastructure and ETL pipelines, and coordinate project operations across a multi-partner, multi-disciplinary team.

The ideal candidate has:

• a strong background in agricultural or environmental data science, with hands-on experience leading research projects and performing data management and analysis;
• experience supervising students and coordinating across multi-partner projects;
• knowledge of virtual farm management systems (LiteFarm) and tools for data-driven agroecology;
• proficiency with databases, data infrastructures, and ETL pipelines; and
• experience engaging with diverse stakeholders on collaborative, community-facing research initiatives.

Organizational Status

Reports to and works closely with Dr. Hannah Wittman (Faculty of Land and Food Systems) and Dr. Khanh Dao Duc (Mathematics). Collaborates with co-investigators, student researchers, and external partners on joint research initiatives. Hires and supervises up to 4 seasonal student interns and/or Work Learn students per year.

Work Performed

The position encompasses three primary areas of responsibility:

A. Bilingual Decision-Support Dashboard & Reporting Stack

• Architect, develop, and maintain a bilingual (English/French) open-source decision-support dashboard using Shiny for Python/R, compliant with current accessibility standards (WCAG, keyboard-only navigation, color-blind friendly palettes).
• Implement farmer-facing reporting workflows: fetch existing LiteFarm farm management data, trigger GHG emission calculations and RegenScore assessments via API, and deliver personalized sustainability reports through the LiteFarm platform.
• Build researcher and public-facing dashboard views with tiered access (public aggregates, research views, secure organizational dashboards), scenario modelling for climate projections, and downloadable datasets with uncertainty bounds.
• Maintain dashboard quality assurance, incorporate stakeholder feedback from workshops, and lead iterative releases toward the Year 5 bilingual production launch

B. Data Infrastructure, ETL Pipelines & Common Farm Convention Alignment

• Design, implement, and maintain secure, CFC-compliant (Common Farm Convention) data infrastructure for the LiteFarm database and other research repositories, including automated quality-control checks to flag anomalous values.
• Build and maintain ETL pipelines that integrate core LiteFarm farm records (~1.2 million and growing) with six environmental data layers: climate, soil (SoilGrids), biodiversity, satellite imagery, terrain, and survey results.
• Support translation of farm attributes and units across GHG modelling tools (Cool Farm Tool, Holos) and coordinate schema conformity reviews with partners (OurSci, OpenTEAM, AAFC, CFT).
• Support HQP (graduate students, USRAs, Work Learn) in building and maintaining data pipelines; ensure all pipelines are open-source, reproducible, and extensible to additional calculators and emission models.
• Perform data harmonization, wrangling, and analysis on a broad range of agricultural datasets in support of research objectives across the project team.

Consequence