Digital Data Analyst

Harnham
Burton upon Trent
1 month ago
Applications closed

Related Jobs

View all jobs

Data Analyst/ Consultant (SuccessFactors, MS Excel, Mapping)

Senior Data Analyst

Senior Data Analyst

HR Data Analyst - Kempston

Senior Data Analyst

Data Analyst

Digital Data Analyst – Up to £45,000

Burton Upon Trent – Hybrid (1-2 days per week in office)

A growing analytics team is hiring aDigital Data Analystto optimize web performance, track user behavior, and provide real-time insights across 80+ websites. This is a hands-on role, working withSQL, GA4, Looker, Power BI, and Excelto assess data quality, debug tracking issues, and generate reports that drive key business decisions.

The Company

A well-established brand in thehospitality sector, operating over2,600 pubs, restaurants, and hotels across the UK. Their digital analytics function is expanding to enhancewebsite performance, customer journeys, and marketing effectiveness.

The analytics team is structured into four key areas:

  • Digital– Website and app reporting, deep-dive analysis, and future planning
  • CRM– Customer database management, campaign analysis, and reporting
  • Loyalty & Customer Insights– Understanding and segmenting customer behavior
  • Data Science & Engineering– Supporting analytics efforts and proving business value

The Role

As aDigital Data Analyst, you will be responsible for website performance analytics, ensuring high-quality data reporting and debugging tracking issues. You will provide valuable insights that enhance the customer experience and improve conversion rates.

Key Responsibilities:

  • Ensure data quality and debug tracking issues for web analytics tools such as GA4, Looker, and Power BI
  • Extract, assess, and report on website data, delivering actionable insights
  • Work with SQL to manipulate and analyze datasets
  • Build automated dashboards and reports to track website performance
  • Support conversion rate optimization (CRO) initiatives by identifying drop-off points in customer journeys
  • Work with marketing and product teams to optimize digital campaigns and user experiences

Your Skills and Experience

The ideal candidate is a web analytics professional with strong technical expertise and the ability to turn data into insights.

Essential:

  • Strong SQL skills with experience in extracting and transforming web data
  • Experience with GA4 (Google Analytics), Looker, and Power BI
  • Understanding of website tracking, tag debugging, and data validation
  • Proficiency in Excel for manual reporting where necessary
  • Ability to interpret data trends and make recommendations

Nice to Have:

  • Experience with Microsoft Clarity
  • Knowledge of CRO and website optimization strategies
  • Background in Adobe Analytics (not required but beneficial)

The Benefits

  • Salary up to £45,000
  • Hybrid working with 1-2 days per week in Burton Upon Trent
  • Exposure to a high-growth analytics function
  • Collaboration with Data Science, CRM, and Marketing teams
  • Strong career progression opportunities

How to Apply

Please register your interest by sending your CV toMohammed Buhariwalaat Harnham via the Apply link on this page.

Key Terms

Digital Analyst, Web Analytics, SQL, GA4, Google Analytics, Looker, Power BI, Microsoft Clarity, Data Visualization, CRO, Dashboarding, Reporting, Data Science, Customer Insights, Tag Debugging, Conversion Rate Optimization, Hospitality Analytics, Burton Upon Trent, Hybrid Work.

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.