Business Intelligence Developer

Eurobase People
London
8 months ago
Applications closed

Related Jobs

View all jobs

Business Intelligence Developer

Business Intelligence Developer

Business Intelligence Developer

Business Intelligence Developer

Business Intelligence Developer

Business Intelligence Developer

Get AI-powered advice on this job and more exclusive features.

Eurobase People provided pay range

This range is provided by Eurobase People. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Direct message the job poster from Eurobase People

Recruitment Team Manager at Eurobase People

I'm currently partnering with a client of mine who are looking for a strong Tableau Developer to come on board to deliver on key projects. They are reviewing profiles right away with a view of starting someone immediately. As a Tableau Developer you should have a demonstrated ability to design engaging and interactive business insight dashboards using Tableau and possess extensive knowledge and experience of data visualisation best practice. This is a specific Tableau Development position.

Job Profile

Developing, maintaining, managing advanced reporting analytics, dashboards Solutions in Tableau

Dashboard creation, troubleshooting, data source management Create and edit SQL Queries within Tableau Create Interactive Filters, Parameters and calculations

Collaborate with business users

Reviewing and improving existing systems

Understanding of LOD

They are reviewing profiles right away with a view of starting someone immediately. If you would like to discuss this role further call me Subeg Lehl or send me a latest copy of Your CV

Seniority level

  • Seniority levelMid-Senior level

Employment type

  • Employment typeFull-time

Job function

  • Job functionConsulting
  • IndustriesInsurance, Financial Services, and Professional Services

Referrals increase your chances of interviewing at Eurobase People by 2x

London, England, United Kingdom 3 days ago

London, England, United Kingdom 3 weeks ago

London, England, United Kingdom 8 months ago

Senior Business Intelligence (BI) Developer

London, England, United Kingdom 1 month ago

London, England, United Kingdom 3 months ago

London, England, United Kingdom 4 days ago

Senior Director, Gartner Analyst, Data Centers (Remote EMEA)

London, England, United Kingdom 1 week ago

Senior Director Analyst, Data & Analytics Governance (Remote Europe)

London, England, United Kingdom 5 hours ago

Director Analyst, Master Data Management (MDM), Remote

London, England, United Kingdom 1 week ago

Remote Dynamics NAV/BC Developer - Mobile WMS / Inventory SaaS for NHS

London, England, United Kingdom 2 hours ago

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#J-18808-Ljbffr

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.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.