GIS Specialist

GIS Specialist

Reporting to: Principal Data Engineer

Role Overview

To develop the geospatial data foundation, utilising our data mesh and bringing together geospatial datasets, EO and internal data to create a scalable spatial data solution. The outputs will provide Group wide intelligence and actionable insights to ensure the most effective and sustainable use of land.

A key focus will be moving geospatial processing from manual GIS workflows towards automated, maintainable and production-ready data pipelines that can support digital products, analytics and AI/ML applications.

Key responsibilities

Land Use Intelligence

Develop and maintain Origin’s spatial data framework.

Integrate national and regional datasets covering areas such as land use, land cover, field boundaries, land ownership, soils, topography, water, habitats, environmental designations and planning constraints.

Develop spatial rules and analytical approaches for automatically characterising fields, land parcels and landholdings.

Input into the ongoing development of a solution that connects land characteristics, opportunities and constraints with relevant products and services across the Group.

Develop repeatable approaches for identifying and screening land opportunities at regional and national scale.

Work with domain specialists to ensure spatial classifications and analytical rules are appropriate for agricultural, environmental and land-management applications.

Geospatial data engineering & Data Mesh

Work closely with the Principal Data Engineer and Data Mesh team to define how spatial data is ingested, represented, stored, catalogued and distributed within Origin’s data architecture.

Design automated pipelines for ingesting, transforming, validating, classifying and refreshing geospatial datasets.

Develop reusable spatial data products that can be consumed by applications, analytics, APIs and AI/ML services.

Establish appropriate spatial data standards covering coordinate systems, identifiers, topology, metadata, lineage and data quality.

Help establish consistent relationships between fields, land parcels, customers, landholdings and other spatial entities.

Support integration of spatial data with internal customer, operational and commercial datasets.

Ensure geospatial workflows are scalable and reproducible rather than dependent upon manual desktop GIS processing.

Work with engineering teams to operationalise successful GIS prototypes.

GIS & spatial analysis

Undertake advanced spatial analysis including intersection, proximity, suitability, terrain and hydrological analysis.

Develop automated spatial workflows using Python, SQL and appropriate geospatial libraries.

Work with vector, raster and point-cloud/elevation datasets.

Develop methods for assessing spatial data quality, completeness and accuracy.

Support prototyping and visualisation using tools such as QGIS where appropriate for other ad-hoc use cases as and when they arise.

Earth Observation

Support the incorporation of Earth Observation-derived information into Land Use Intelligence.

Work with optical and other EO-derived datasets including Sentinel imagery.

Understand and utilise common EO outputs such as vegetation indices, land-cover classifications and change-detection products.

Work closely with the Earth Observation & GeoAI Specialist to define how EO outputs are linked to fields and other spatial entities.

Help establish appropriate mechanisms for storing and distributing EO-derived outputs through the Data Mesh.

Essential skills and experience

Professional experience in GIS, Geospatial Data Science, Geospatial Engineering or a related discipline.

Strong understanding of vector and raster geospatial data.

Experience working with cloud-based data architectures, ideally AWS.

Strong experience with GIS platforms such as QGIS, ArcGIS or equivalent.

Experience working with spatial databases, ideally PostGIS.

Python experience for geospatial automation.

SQL experience.

Experience with geospatial libraries and tools such as GeoPandas, GDAL, Rasterio, Shapely or equivalent.

Experience processing large regional or national spatial datasets.

Experience designing repeatable spatial ETL/data-processing workflows.

Strong understanding of coordinate reference systems, topology, spatial accuracy and data quality.

Experience consuming APIs and geospatial web services.

Ability to translate business requirements into spatial analytical rules.

Working knowledge of Earth Observation and satellite imagery.

Desirable skills and experience

Experience within agriculture, environmental management, natural capital or land management.

Experience with UK spatial datasets such as Ordnance Survey, OpenStreetMap, Land Registry, Defra or Environment Agency data.

Familiarity with data lakes, data meshes or modern enterprise data architectures.

Experience with Sentinel-1 and/or Sentinel-2.

Sentinel Hub or comparable EO-platform experience.

Experience with LiDAR and terrain/hydrological analysis.

Familiarity with spatial machine learning or GeoAI.

Experience publishing spatial data through APIs or web applications.

Understanding of spatial data licensing and governance.

Who are we?

Origin Digital is an agricultural technology company that develops advanced agronomy software to help farmers and agribusinesses make better decisions. Our platforms provide field-level planning, crop performance monitoring, remote sensing, and predictive insights that improve farm productivity, sustainability, and profitability. You can find out more at https://digital.originenterprises.com/