Principal Software Engineer @ Leonardo

October 2025 - present

Lead engineer for Leonardo's Data & Analytics team, transforming a fragmented engineering function into a product-driven team delivering data capabilities to customers. Tech includes Python, REST microservices, Docker, CI/CD.

• Led the design and delivery of an asynchronous REST microservice data platform with distributed pipelines capable of cataloguing and replaying petabytes of historical geolocated data, accelerating algorithm development by orders of magnitude.

• Established version control discipline, containerisation standards, and a CI/CD pipeline — compressing feature delivery from months to days.

• Founded an engineering guild and upskilled colleagues through pair programming to embed architectural principles and testing practices across the organisation.

• Line manage several engineers and mentor industrial placement students through tailored development plans and technical coaching.

Senior Engineer @ Sylvera

April 2023 - October 2025

Senior engineer within the Earth Analytics team, mentoring a team of engineers to scale Sylvera’s geospatial products and unlock new revenue streams, with a target contribution of one- third of the company’s annual recurring revenue. Tech includes Python, C++, Typescript, AWS, Docker, Terraform.

• I lead the design of a new external service, collaborating across teams and engaging with customers to deliver proprietary data to the market for the first time.

• I modernised engineering standards, mentored colleagues and consolidated a fragmented codebase into a platform - providing a launchpad to scale the business to the next level.

• I led a team to productionise and automate 25 manual geospatial products. This reduced data delivery times from over a week to an averageof 30 minutes and increased the volume of delivery from around 5 projects a week toin order of hundreds.

• Contributed to novel ML techniques applied to satellite data for above ground biomass mapping that have been published in scientific journals.

Data Scientist & Engineer @ Babcock LGE

October 2022 - March 2023

Leading the development of data processing pipelines and methodologies to analyse real time data streamed remotely from Liquid Gas Equipment (LGE) instrumentation. Tech included C#, Python, Typescript, AWS and Docker.

• Leading the deployment of the infrastructure and practices required to productionise remotely monitored instrumentation data into commercial products. This is a new endeavour for Babcock and I liaised with business wide stakeholders to ensure solutions work across the business and remain robust

• Developing machine learning and artificial intelligence solutions to minimise operational downtime and ensure equipment is running efficiently as possible; aiding the shipping industry in meeting its net zero commitments

• Developing digital twins of instrumentation to aid process (chemical) engineers understand how systems are operating in the field

• Wrote the job descriptions, interviewed and grew the team from myself whilst also incorporating with the wider business graduate scheme

Data Scientist @ Earth Blox

March 2022 - August 2022

(Part time whilst doing Masters) Data scientist at a fast paced startup aiming to make earth observation accessible to everyone, regardless of expertise. I support the development of new earth observation workflows by developing data science pipelines and prototyping new algorithms. Tech included Python, Typescript, Google Cloud, Earth Engine.

• Led the design and implementation an automated testing framework for the earth blox application.

• Collated historical windthrow events from the Copernicus Emergency Management Service to facilitate development of new windthrow algorithms in Sentinel-1 data.

Software Engineer @ Kratos Analytical

Dec 2020 - Aug 2021

Responsible for feasibility studies and driving the adoption of new technologies/practices. Tech included C++, C#, Azure, Specflow, Gherkin, Appium.

• Developed a test framework with the capability to automate at least 50% of the existing manual testing

• Incorporated Azure into the existing infrastructure to improve CI/CD

• Migrated the existing C++ codebase to C++17 and incorporated modern C++ practices into the codebase such as smart pointers, lambdas and auto type inference and STL containers to improve code readability and maintainability

Software Engineer @ Waters

Nov 2017 - Dec 2020

Responsible for the design and implementation of Mass Spectrometer control software. Working within a microservice architecture with C++, C#, embedded Lua, Docker, Angular2+

• Created deep simulations of real time data and instrument behaviour to aid in the development of new control software.

• Incorporated rust into the existing gRPC C++ microservice architecture to improve robustness and reduce bugs.

• Led the development a new realtime "Health" service to monitor the health of the mass spectrometer and alert users to potential issues.

• Automated complicated, previously manual, instrument setup procedures to make the instruments more accessible to less technical users.

Development Scientist @ Waters

Jun 2016 - Sep 2016

Involved in the development process and testing of a new mass spectrometer.

• Carried out component and sub-system testing on a prototype mass spectrometer

• Gained knowledge in maintaining mass spectrometry systems, specifically with GC-MS systems

• Suggested design improvements in relation to potential faults and liaised with mechanical engineers in Singapore about these issues

2021 - 2022

Developed a thorough understanding of machine learning/statistical methodologies and how to apply these to scientific data. For my dissertation, Segmentation of Windthrow in High Resolution Capella SAR Images Using Fully Convolutional Networks, I developed tools to automate the processing of SAR imagery into a format suitable for deep learning and developing novel segmentation algorithms. This work was supervised by Prof Iain Woodhouse and I worked closely with Capella Space. Courses Included:

• Achieved an MSc with Distinction

• Dissertation Mark 87%

2014 - 2017

Gained an understanding of many physical systems and excellent mathematical abilities in areas covering calculus, linear algebra, mathematical reasoning, probability and statistics.

• Achieved a First Class degree

• Developed a Least-Squares Fitting Routine Python application currently in use by the University for data analysis and received formal recognition from the Laboratories Committee for the ‘outstanding’ work done and its usefulness for studies in Undergraduate Laboratory work

2013 - 2014

Progression from foundation year required an average year grade of 80% which was achieved by averaging 93%; amongst the highest in my cohort.

• Recipient of the Gillett Foundation Studies Scholarship, this was awarded in recognition of my achievements on foundation year

Ambient Gamma UK @ personal

A live map of ambient gamma radiation across the UK, visualising real-time data from the UKHSA RIMNET monitoring network.

⚡️ Zapp 🐍 @ github

Zapp is a Python tool to automatically generate and maintain python module interfaces. Zapp is inspired by the modular monolith architecture and is designed to compliment the awesome tach package.

• Open source and free to use! 🌍

• Written in rust 🦀

• Installed via pip 🐍