Data Engineering

Every hour spent manually wrangling data is an hour not spent on analysis and decision-making.

For environmental monitoring programmes generating continuous streams of satellite imagery, sensor readings, camera trap photos, or survey data, manual processing quickly becomes the bottleneck that limits what’s possible.

I build automated pipelines tailored to environmental data contexts. This includes ETL systems that collect data from multiple sources and standardise it for analysis, automated quality assurance that flags anomalies before they corrupt downstream work, and workflow orchestration that chains processing steps together reliably. When working with WildMon, I built infrastructure that reduced new project setup from several days to a few hours—automatically collecting and processing satellite data for any study area globally.

The goal is always removing repetitive work so your team can focus on the ecological questions that actually require human expertise. A well-built pipeline also ensures consistency: every dataset processed the same way, every time, eliminating the errors that creep in when preparation is done manually.

Next Step

Would you like to schedule a brief chat to outline your current data workflow and explore how an automated pipeline could free up your time for critical ecological analysis?