Job Description: Data Engineer
Location: London/Hybrid – Office two+ days per week
We’re hiring data engineers who want to take ownership in a fast-scaling startup
About Clariti AI
Clariti AI is a B2B SaaS company providing price optimisation software to retail banks. We help banks make pricing decisions on products like mortgages and savings. Our pricing software guides clients to price recommendations that are worth millions of Pounds or Euros in additional revenue.
This is an exciting time to join the company, with a growing set of clients in the UK and Ireland. After recent successes, Clariti AI has built a very promising pipeline of new clients, with revenues expected to increase significantly in the next year. The company is bootstrapped (no VC or angel investment) and is already very profitable.
Data Engineer
This data engineer role will play a key role in helping us improve the production quality of our software as we scale. Our software offering has a significant financial impact for our clients and needs to be outstanding for our clients to get value.
As an early joiner, the Data Engineer role is key, and provides multiple opportunities for the right person to grow significantly. There are many things to focus on depending on experience and interests. The role is all about pro-active "building and improving", whether that is scaling our infrastructure as we take on more clients and larger clients, streamlining and automating data refresh processes, improving our data security, building and deploying machine learning models, or getting involved with client pitches.
What you'll be working on
Building, optimising, and deploying price optimization machine learning ETL/ELT pipelines and data processes.
Improving and adapting our data infrastructure and code base as we scale – including collaboration, security, scalability, efficiency, automation and auditability.
Interacting with new clients on client pitches, and working with existing clients to onboard our software, offering engineering and pricing expertise.
Essentials:
Strong academic background with a minimum bachelor’s or master’s degree in a STEM subject (Computer Science, Mathematics or Engineering)
At least 2 years’ experience working as a data engineer (ideally consulting / financial services) – salary and level will reflect experience.
Proficiency in Python (pandas, numpy)
Professional experience with Azure cloud services (AWS / GCP acceptable with deeper experience)
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