About Us

Digital Wombat is led by Ben Middleton, a software consultant at TNG Technology Consulting. This page outlines Ben's academic and professional career and experience.

Work Experience

💼Software Consultant
TNG Technology Consulting · Full-time · Munich, Bavaria, Germany · Hybrid
Oct 2023 to Present
Backend Development:
  • Develop internal applications and REST APIs in Python3 to support multiple departments.
  • Create internal automation tools and REST APIs in Go.
Frontend Development:
  • Develop internal self-service portals and applications using TypeScript, React, and Material-UI.
  • Led the migration of ~20,000 lines of TypeScript/React code to more modern frameworks using AI agents to accelerate refactoring and improve maintainability.
Cloud Infrastructure & DevOps:
  • Manage and optimize AWS infrastructure and Kubernetes clusters in AWS EKS.
  • Design and maintain CI/CD pipelines using Tekton and Github Actions.
  • Provision and manage infrastructure using Infrastructure as Code (IaC) with Terraform, Helm, and Helmfile.
  • Operate and monitor containerized applications using k9s.
SSO & Security:
  • Operate Keycloak as the central authentication and authorization platform for internal and external services.
  • Maintain a company-wide SSO solution supporting over 800 users.
Network & System Administration:
  • Administer network infrastructure, server management, and modern firewall management across multiple locations.
  • Server configuration and provisioning with Ansible.
  • Manage various internal systems and tools: LDAP, VPN, DNS, PGP and cloud access control system.
Team Collaboration & Knowledge Sharing:
  • Onboard new team members and foster knowledge dissemination within the team.

Education

🎓MPhys Physics
University Of Oxford
October 2018 - June 2023
Final results:
  • Passed with First Class Honours, final mark 82%.
  • Ranked 4 out of 97 students.
Final year project:
  • Title: Machine Learning For Live-cell Super-resolution Imaging.
  • Retrained a neural network to improve the resolution of bacterial images taken with a light microscope. The system made use of a Generative Adversarial Network (GAN) which trained a U-net generator against a Convolutional Neural Network discriminator.
  • Received a distinction for this piece of work.
Additional achievements:
  • Distinction in preliminary examinations – 5th highest mark in the year of 177 students
  • Distinction in second year examinations – 2nd highest mark in the year of 175 students.
  • Awarded "The Scott Prize" for performance in the Physics Second Year Examination.
  • First class in third year examinations – 2nd highest mark in the year of 157 students.
  • Awarded "The Gibbs prize" for performance in the MPhys Examination

Ready to Start Your Project?

Let's discuss how we can help bring your vision to life with innovative technology solutions.