GIS Developer

1w1 week ago

Verisk

Bath, GB · Full-time · £50,000 – £75,000

About this role

Verisk Maplecroft are looking for a Data Engineer who thrives on building efficient, bespoke and high-impact data pipelines. You will build and maintain automated pipelines for continuous delivery of risk index data forming Maplecroft’s Global Risk Data. This role focuses on geospatial data workflows in geosciences and risk analytics.

Design, build, and optimize data pipelines with Python to handle acquisition, transformation, and manipulation. Streamline and scale workflows using Metaflow, Prefect, AWS, and proprietary data services. Deliver high-quality, maintainable, well-tested code meeting business requirements.

Collaborate with data scientists, analysts, and developers for seamless data flow and bespoke methodologies. Improve data quality, reliability, and accessibility across teams. Enable a consistent approach to data production pipelines in a collaborative Agile environment.

At Verisk, use your voice and build a rewarding career with work flexibility, support, coaching, and training. Verisk is recognized as a Great Place to Work® in the UK and values inclusivity, diversity, learning, caring, and results. Join 7,000 people pursuing innovation in data analytics for the global insurance industry.

Requirements

Proven track record of developing in Python
Applied understanding of good data acquisition, transformation and manipulation techniques
Familiarity working with geospatial data within Python (GDAL, rasterio, shapely)
Established experience of building ETL frameworks and tooling
Knowledge of common Python data analysis libraries (numpy, pandas)
Familiarity with Agile software development practices
Good understanding of git and working collaboratively on team-level code base
Knowledge of cloud technologies and platforms such as AWS

Responsibilities

Design, build, and optimize data pipelines with Python
Streamline and scale data workflows using Metaflow, Prefect, AWS and proprietary data services
Collaborate with data scientists, analysts, and developers to ensure seamless data flow and implementation of bespoke company methodologies
Improve data quality, reliability, and accessibility across teams
Deliver high-quality, maintainable well-tested code that meets business requirements
Enable a consistent approach to data production pipeline