Business Intelligence Analyst

JW Lees
Hartlepool
1 year ago
Applications closed

Related Jobs

View all jobs

Trainee Data Analyst/Support – Training Course

Data Analyst Training Course (Excel, SQL & Power BI)

Data Analyst (GenAi) KYC

Process & Performance Data Analyst

Data Analyst (Engineering)

Performance Data Analyst

Business Intelligence Analyst Vacancy – Up to £33,000 - Middleton, Manchester

This is an office based role

JW Lees has an exciting opportunity for a Business Intelligence Analyst to join the Financial
Data and Analytics Team based at our Greengate Brewery in Middleton, Manchester.

What’s in it for you as a Business Intelligence Analyst:

  • Competitive pay - Up to £33,000
  • Private medical cover with BUPA
  • Profit share
  • Enhanced family friendly policies
  • Access to BenefitHub offering online and high street discounts
  • Discount in all our managed pubs, inns and hotels
  • Access to our employee assistance programme
  • Yearly service recognition
  • Annual party and conference

Role & Responsibilities:

  • Support the Financial Data and
    Analytics team on the exciting journey of implementation of Power BI into the
    business.
  • Continued
    development of reporting using Power BI, collaborating with business users to understand
    requirements and deliver customised reporting.
  • Support with completing and
    continuously developing current weekly / monthly / annual Excel based reporting.
  • Support with ad hoc data
    reporting and analysis based on stakeholder needs.
  • Analytical approach to data with
    a view to offering insight and highlighting opportunities that support the
    business’ strategy.
  • Ensure the accuracy, consistency,
    and reliability of all delivered data outputs.
  • Stay informed on the latest
    trends and best practices in data visualisation and reporting.

The Person



  • Solid commercial experience of
    having worked as a Business Intelligence Developer using Power BI.
  • Strong experience of using Power
    BI to create management dashboards from multiple data sources.
  • Strong experience of using Microsoft
    Excel to create reporting.
  • Experience of understanding and
    visualising financial data is preferable.
  • Ability to build solid working
    relationships with colleagues at all different levels.
  • Effective workload management and
    organisational skills to ensure that deadlines are met, and productivity is
    maximised.
  • Good team player, with
    self-motivation and drive.














 Required Skills



  • Excellent analytic
    and problem-solving skills.
  • Data visualization and
    storytelling.
  • Experience of
    reporting through Power BI.
  • DAX knowledge
    preferable but not essential.
  • Understanding of Power
    Query preferable but not essential.
  • Basic SQL knowledge
    desired but not essential.
  • Microsoft Excel.
  • Strong communication
    and people skills.
  • Strong attention to
    detail.
  • Ability to work
    independently and in a team environment.

About JW Lees:

Proudly family owned and nearly 200 years old, JW Lees are the original modern, traditional brewer. With 150 pubs, inns and hotels across the North West and North Wales, we are passionate about great beer, fantastic food and memorable experiences.

We put people at the heart of our business, always doing the right thing and always sticking together. Our six values are at the heart of everything we do:

Proud  -  Savvy  -  Honest  -  Passionate  -  Personal  -  Together

































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.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.