Data Engineer

Step 2 Recruitment; Greater London; Hybrid; GBP 60,000 - 95,000; Full time

Benefits offered by this job

Profit sharing

Equity options

Flexible working hours

Work anywhere for up to two months a

25 days holiday

Job summary

Clariti AI is a London-based startup hiring a Data Engineer to scale price optimization software for banks. You will own data pipelines and contribute to production-grade data infrastructure in a fast-growing environment.

As an early joiner, you’ll work on ML ETL/ELT pipelines, scale infrastructure, improve security, and support client pitches with engineering and pricing insights. Flexible hours and travel to client sites offered.

Qualifications

• Minimum bachelor’s or master’s degree in a STEM subject (CS, Mathematics or Engineering).
• At least 2 years’ experience as a data engineer (ideal in consulting/financial services).
• Proficiency in Python (pandas, numpy).
• Professional experience with Azure cloud services (AWS/GCP acceptable with deeper experience).
• Strong experience deploying clean, maintainable, production-level code.
• Basic understanding of DAGs and their role in pipeline orchestration.

Responsibilities

• Build, optimise, and deploy price optimization ML ETL/ELT pipelines and data processes.
• Improve and adapt data infrastructure and codebase as we scale, focusing on security, scalability and automation.
• Interact with new and existing clients on pitches, onboarding and providing engineering/pricing insights.

Skills

Data engineering

Python

DAG workflows

Client pitches

Cloud computing

Education

Bachelor's or Master's in STEM

Tools

Azure

AWS

GCP

Docker

Kubernetes

Airflow

Dagster

MySQL

PySpark

SQL

Job description

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)
• Strong experience deploying clean, maintainable, production-level code.
• Basic understanding of DAG (Directed Acyclic Graphs) and their role in pipeline orchestration

It would be nice if you could bring (desirables)

• Professional experience with PySpark, MySQL, Docker, Kubernetes
• Experience with best-practice pipeline orchestration software (Airflow, Dagster).
• Experience migrating code from prototype notebooks to .py, while maintaining logic and transparency of underlying code
• Owned a project across a whole software product lifecycle, from data infrastructure, to model development and deployment, to front-end integration
• Experience of pricing analytics and/or optimization ideally in retail banking
• Experience in producing PowerPoint presentations / reports and presenting to clients or colleagues
• Willingness to get involved in all parts of the business – we are a small company so we all wear many hats
• An entrepreneurial spirit and drive to work in an early-stage start-up that directly rewards impact

Tech stack:

• Platform: We build everything in Azure (but sometimes need to work in other cloud providers like AWS depending on client’s needs).
• Backend – We develop all our code in Python
• Front-end – MySQL and jQuery/React

What we offer

• A highly competitive salary
• A genuinely compelling profit share scheme, with the potential to own a significant stake in the business
• Equity options that deliver significant gains if the company is acquired
• Flexible working hours
• “Work anywhere” for up to two months a year
• A significant opportunity to grow quickly with regular performance-based promotions and pay increases
• 25 days per year holiday allowance, increasing by one day per year after two years’ service to 30 days

Other

• We cannot sponsor visas, so only applicants with the permanent right to work in the UK will be considered
• Successful applicants should be willing to work in London up to two days a week and should be willing to travel to clients occasionally