Smith Institute uses advanced mathematics, AI and data science to help customers do some amazing things – like balance the electricity grid, optimise satellite communications and safeguard multi-billion-dollar 5G spectrum auctions. 

We are seeking an enthusiastic Data Engineer to build future-proof pipelines and uncover deep insight from customer data across all our sectors. You will be engaged in multiple projects at any one time, working with our Mathematical Consultant teams and directly with customers to design, build and exploit the data architecture needed to deliver on our ambitious goals. 


  • Design and build robust end-to-end data pipelines, both locally and in the cloud, for projects requiring clean, ready-to-model data derived from multiple disparate raw sources. 
  • Advise on system, data and model architecture in early-stage opportunity scoping. 
  • Ensure data is stored in the most appropriate and proportionate system for its intended purpose. 
  • Clean and summarise datasets, probe their content and integrity, and produce exploratory analyses of their content. 
  • Work on multiple projects simultaneously as a key member of engineering staff. 
  • Stay abreast of relevant tools and techniques in data-driven modelling. 
  • Collaborate in raising the technology readiness level of proofs-of-concept, building exploratory notebooks and scripts into repeatable, performant, future-ready pipelines. 
  • Contribute to the wider design and development of mathematical and statistical models. 
  • Be an expert voice in wider company processes and policies around data and engineering. 

Necessary qualifications, skills and experience: 

  • Bachelor’s degree in a scientific or engineering discipline, with master’s or doctoral-level study preferred 
  • Expert Python programmer 
  • Linux and Windows environments 
  • Version control via Git 
  • Unit and integration testing 
  • Cloud platforms and data services 
  • Relational databases and SQL 
  • Data cleaning, merging and manipulation, including feature engineering 
  • Exploratory data analysis and data visualisation 
  • Building and deploying repeatable ETL pipelines 
  • Teamwork, multi-tasking, and distributed working 

Experience in some but not all of the following would also be expected: 

  • Other programming languages (particularly R) 
  • Professional software engineering 
  • Machine learning model design and development 
  • MLops infrastructure for model deployment 
  • DevOps processes, including CI/CD 
  • Containerisation 
  • Web development, especially front-end frameworks (such as React) 
  • Dashboarding systems (such as PowerBI) 
  • Distributed processing of big data 
  • NoSQL databases and data modelling techniques, such as knowledge graphs 
  • API design, implementation and deployment 

Why work at Smith Institute? 

  • Flexible working for all – work your contracted hours at times that best suit you and our customers, at home, in the office or as a mixture of both 
  • Health and well-being support – Smith Institute provides up to three months’ contractual sick pay, have qualified Mental Health First Aiders, a Mindful Employer Plus membership and offer additional leave allowance to care for close family members 
  • Social events – most months our Social Committee organise events and we also have ongoing activities, including pub socials, a book club, a fantasy football league and a board games library 
  • Employee benefits – employee discount platform and Employee assistance programme 
  • Enhanced leave – bereavement, dependency, maternity, paternity & shared parental leave 
  • Mentoring – from colleagues and leading academics 
  • Generous pension scheme with Life Assurance and income protection 
  • All IT equipment provided and maintained 
  • Interesting and challenging work with purpose 

Excited to work with us? To apply, send your CV and a covering letter to In your letter, please introduce yourself, explain your motivations for applying to Smith Institute, and outline how your background matches our needs. 

Please let us know if there are reasonable adjustments we can make for you to ensure an accessible recruitment process and beyond. Part-time working will be considered.