Data Engineer

Step 2 Recruitment LTD
London, United Kingdom
2 weeks ago
£50,000 – £85,000 pa

Salary

£50,000 – £85,000 pa

Job Type
Permanent
Work Location
Hybrid
Seniority
Mid
Education
Degree
Posted
14 May 2026 (2 weeks ago)

Benefits

Highly competitive salary Profit share scheme Equity options Flexible working hours Work anywhere for up to two months a year

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 thepermanent 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

Related Jobs

View all jobs

Data Engineer

hireful Exeter, United Kingdom
£50,000 – £55,000 pa Hybrid

Data Engineer

Robert Walters Manchester, United Kingdom
£55,000 – £60,000 pa Hybrid

Data Engineer

Orbit Group Binley Woods, Warwickshire, United Kingdom
£43,760 – £54,697 pa On-site

Data Engineer

Pontoon Bristol, Bristol (county), United Kingdom
£600 – £650 pd

Data Engineer

Hays Technology Salisbury, Wiltshire, United Kingdom
£50,000 – £52,750 pa Hybrid Clearance Required

Data Engineer

CBSbutler Holdings Limited trading as CBSbutler Telford, Shropshire, SY2 5TN, United Kingdom
£400 – £450 pd Hybrid Clearance Required

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Data Engineering Jobs in the UK (2026 Guide)

Where to advertise data engineering jobs UK in 2026: the specialist boards and channels that reach Spark, dbt, Snowflake and platform engineering talent. Data engineers occupy a distinct discipline that sits between software engineering, data science and cloud infrastructure — and the strongest candidates identify firmly with the data engineering community rather than with adjacent roles. General job boards consistently conflate data engineering with data analysis, data science and BI development, producing high application volumes but low candidate quality for specialist pipeline and platform roles. This guide, published by DataEngineeringJobs.co.uk, covers where to advertise data engineering roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Data Engineering Jobs UK 2026: What to Expect Over the Next 3 Years

Data Engineering Jobs UK 2026: roles, salaries and the trends shaping UK data engineering hiring over the next three years — Spark, dbt, lakehouse and AI. Data engineering has become one of the most strategically important disciplines in the entire technology sector — and one of the most reliably in-demand. Every organisation that wants to use data to make decisions, train AI models, personalise products, manage risk, or understand its customers depends on data engineers to build the infrastructure that makes any of that possible. Without well-designed, reliable data pipelines, the most sophisticated machine learning model is worthless and the most ambitious analytics strategy is undeliverable. That foundational importance has made data engineering hiring remarkably resilient through the technology market corrections of the past few years. Where headcount reductions fell heavily on some engineering disciplines, demand for data engineers held firm — because the work of building and maintaining data infrastructure cannot be deferred in the way that some product development can. The data keeps coming. The pipelines need to work. But the data engineering jobs market of 2026 is not simply a stable version of what it was three years ago. The discipline has undergone a series of architectural shifts — from batch to streaming, from on-premise data warehouses to cloud-native lakehouses, from hand-rolled pipelines to declarative transformation frameworks, and most recently toward AI-augmented data engineering workflows that are beginning to reshape what the role looks like in practice. The employers hiring data engineers today are asking for a meaningfully different skill set than those hiring three years ago. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which architectural patterns are becoming standard, which technologies are defining the modern data stack, and how the definition of a data engineering career is evolving toward a richer intersection of infrastructure, analytics, and AI enablement. This article breaks down what the UK data engineering jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.