Data & GIS Coordinator

The UW-Madison Arboretum promotes ecologically sustainable relationships between people and the land through research, stewardship, education, and public engagement.

The Data Engineer is a member of the Arboretum’s Research Unit and is supervised by the Research Program Manager/Ecologist. The Data Engineer is expected to work closely with the Research Specialist and Citizen Science Coordinator within the Research Unit as well as staff in the Education, Land Care, and Foundational Units to meet the organization’s data development and management, geo-spatial data collection and analysis, map making, and affiliated instrumentation and software support needs. Sample responsibilities include archiving research data; developing and maintaining searchable databases to support research, land management, volunteer, and donor data; analyzing and visualizing research project data; creating project-based maps; helping to train staff and students; and keeping our GPS and GIS software and technologies up to date.

The Research Unit contributes to the Arboretum mission –“We conserve and restore Arboretum lands, advance restoration ecology, and foster the land ethic”– by ensuring that we conduct, support, and facilitate high-quality research, promote available Arboretum research-based resources and opportunities, and communicate research findings to broad audiences.

The Arboretum is committed to embracing social equity and intentional inclusivity as fundamental parts of everything we do, and to fostering connections to the land among diverse audiences.

RESPONSIBILITIES:

Contributes to a research agenda set by a lead researcher by creating automated processes for preparing and analyzing data at scale.
25% Prepares data sets for current and future analysis including cleaning/quality assurance, transformations, restructuring, and integration of multiple data sources and may use technologies that support data at scale
25% Implements data analysis steps in collaboration with data scientists, statisticians, and/or other researchers and may use technologies that support data at scale
5% Organizes both data preparation and analysis steps into reproducible pipelines that can process similar data sets automatically
15% Selects appropriate technologies and optimizes pipelines for performance
10% Develops, constructs, tests, and maintains architectures for large-scale data management and analysis
15% Creates maps and performs a wide range of geospatial analyses in support of a variety of projects
5% Maintains operational functions of technology systems, including GIS and GPS technologies, to ensure appropriate integration, compatibility, and functionality

EDUCATION:

Required
Bachelor’s Degree in geographic information science, computer science, data science, cartography, urban and regional planning, biology, ecology, or similar field, required

Preferred
Master’s Degree

QUALIFICATIONS:

Minimum requirements:
– At least two years of related professional experience
– Knowledge of Geographical Information System (GIS) and Global Positioning System (GPS) technologies
– Knowledge of database management and architecture principles and best practices
– Ability to behave and communicate in a manner that promotes and fosters a culture of teamwork, inclusion, and cooperation with co-workers, supervisors/managers, students, volunteers, and visitors

Preferred Qualifications:
– Experience identifying, designing, and implementing internal process improvements
– Experience developing and managing geospatial data and metadata in accordance with data management standards and research objectives
– Experience using GIS and GPS to create maps for broad application, including ArcGIS and ArcGIS Pro
– Experience with Trimble GPS hardware and post-processing software
– Experience using Adobe Suite software including Illustrator and InDesign
– Experience analyzing geospatial datasets
– Ability to archive, summarize and support the visualization of research, management, and visitor data
– Experience preparing and managing datasets and implementing data models.
– Experience performing data analysis and interpreting results from multiple data sources.
– Experience with statistical, data visualization and database software such as R, Tableau, and Microsoft Access