Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Business Intelligence Developer

Harrington Starr
Sheffield
9 months ago
Applications closed

Related Jobs

View all jobs

Business Intelligence Developer

Business Intelligence Developer

Business Intelligence Developer

Business Intelligence Developer

Business Intelligence Developer

Senior Business Intelligence Developer

Business Intelligence Developer (x2)| Fintech Start-up (remote) | £50,000 - £60,000 + Benefits


My client is one of Europe’s Leading Financial Services Start-up who specialize in the payments space. Beyond this they have also been voted one of the top 20 technology companies in the whole of the UK.


As they continue to expand, we are now looking for 2 new BI Developers to join their team. You will work closely with cross functional teams including developers, data scientists, product managers, implementation teams and business stakeholders.


Apart from coming into the Northeast office once a quarter to meet with the team, this role can be conducted on a fully remote basis but you must be eligible to work in the UK.


What are we looking for?


  • Design, develop, and maintaining the company's business intelligence solutions using software such as Looker and Snowflake.
  • Experience of working with cloud based BI tools such as data visualisation tools Looker, Power BI, Tableau.
  • Exposure to cloud technologies and principles (AWS/Azure) of designing and developing data solutions on public cloud - AWS/Azure.
  • Establish data quality control mechanisms, including data validation, cleansing, and enrichment procedures, to maintain high data accuracy and reliability.
  • Proficiency in programming languages commonly used for data integration and data analysis, such as Python, R, Java and SQL.
  • Ensure compliance with data governance policies, data privacy regulations, and industry standards throughout the data integration process.
  • Prior experience working in Fintech/Payments would be a big plus.


Apply today or get in touch with me for more info at

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

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

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.