BI Data Analyst

DB Foods Ltd
Poole
11 months ago
Applications closed

Related Jobs

View all jobs

BI Data Analyst

BI & Data Analyst - Power BI & SQL (Hybrid)

Senior Data Analyst — Hybrid, BI & Data Strategy Impact

Senior Data Analyst: Power BI & Data Strategy Lead

Power BI Data Analyst

Lead Data Analyst — Azure, Power BI & Data Modelling

Working Hours: Monday – Friday, 45 hours

Who We Are:

The leading wholesale meat supplier to the butchery and food service industry in the UK, DB Foods Limited supplies a comprehensive range of quality wholesale meat, poultry, game and deli products. We have a proven track record in supplying a diverse customer base including Restaurant Groups, Airlines, Cruise Ships, High Street & Catering Butchers, UK Multiples and Online Businesses.

We are currently seeking a BI Data Analyst to join our IT team. You will be at the forefront of analysing and interpreting data, creating dynamic reports and dashboards and communicating findings to the IT Manager.

What We Offer:

  • Life Assurance Policy
  • Discounted meat hampers
  • Employee Assistance Programme which includes offers and discounts for shops and restaurants
  • Growing company with career progression opportunities within the DB Foods Group

Responsibilities:

  • Design and maintain our reporting infrastructure, deliver new reports, monitor performance, and ensure seamless data extraction and transformation.
  • Work closely with business leads to gather, interpret, and develop reporting requirements, ensuring our systems meet their needs.
  • Develop tools to combine data from multiple sources, creating a unified view for better decision-making.
  • Build and maintain dashboards that showcase activity, trends, and projections for operational and strategic insights.
  • Implement improvements to maximise data quality, identifying and resolving issues swiftly.
  • Provide technical expertise in data management and reporting, becoming the go-to expert in reporting systems.
  • Generate significant intelligence reports to support managerial decision-making, ensuring data is well-documented and referenced.
  • Apply technical skills to interpret complex data models, identify quality issues, and derive actionable insights.
  • Summarise complex data analysis and present findings to various audiences, making strategic recommendations.

Skills and Experience:

  • Understanding of SQL databases and data warehouses.
  • Advanced knowledge of PowerBI, SQL, Excel, SSRS.
  • Ability to produce and present data analysis tailored to various users and technical levels.
  • Competent in interpreting and presenting complex data for strategic decision-making.
  • High numeracy and analytical problem-solving skills.
  • Excellent communication and teamwork abilities to develop and maintain reporting systems.

Behaviours:

  • Able to communicate effectively with others.
  • Proven ability to work independently or within a team environment.
  • Capable of working under pressure in a busy environment.

#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.

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.

Careers Jobs

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

🍪 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.