BI Data Engineer - Hotel Chocolat

Datatech Analytics
Royston
1 year ago
Applications closed

Related Jobs

View all jobs

Azure Data Engineer: Power BI & Data Factory Expert

Hybrid CMDB & Power BI Data Engineer

Senior Data Engineer

Lead Data Engineer – Data Warehouse

Data Engineer

Data Engineer

BI Data Engineer – Hotel Chocolat


Hybrid working - 2 Days per week in office Hertfordshire/Cambridgeshire borders


Negotiable DoE £40,000 to £50,000 plus benefits


Job Reference J12900


No sponsorship available for this opportunity


As we continue our mission tomake people and nature happy through chocolate, we’re looking for aData Engineerto join our IT Team on apermanentbasis.


ROLE OVERVIEW


Reporting to the Senior Data Manager, the role of the Data Engineer is to provide support to the business as part of the go-to team for datasets, dashboards, and reports as well as creating bespoke datasets and data translation between systems.

You’ll be part of a data-driven transformation and play a crucial role in shaping the future of how Hotel Chocolat uses data.

The Data Engineer is responsible for ensuring the optimal operation of data pipelines across Production, Test, and UAT to support numerous business applications.

In addition to supporting the business, the Data Engineers support the IT Operations team in fixing data related issues and provide support training on new solutions. The team also provide support with GDPR requests.


JOB ROLE AND RESPONSIBILITIES


  • Maintaining single source of truth so there is one set of data that can be used by varying reporting audiences to achieve their business request/need
  • Develop data models and reports to meet business needs, proactively working with the business to ensure they are created to maximise the opportunity and functionality available
  • Migration of existing data flows to the single source of the truth in either dataset, dashboard, or reporting form
  • Perform data quality tests and reviews against the Production, Test, and UAT data sources to ensure data integrity and optimal performance
  • Proactively engage with key business stakeholders on a regular basis to ensure the data assets managed by the Data team are maintained in-line with business needs
  • Engage with 3rd parties in the provision or consumption of business data
  • Support data consumers in the business by ensuring their use of data tools meet our defined standards and support on how to use these tools so they can consume data with minimal on-going support
  • Maintain documentation related to the datasets to ensure auditing and data dictionaries are accurate


SKILLS AND EXPERIENCE


Essential

  • Demonstratable experience with Microsoft SQL Server i.e. SQL, SSAS, SSRS and SSIS
  • Demonstratable experience of Data Warehousing and ETL
  • Experience of taking business requirements and translating these into user consumable data sets, dashboards and reports
  • Exposure of merging data sets from different solutions to form one unique data set

Desirable

  • Experience of database management tasks and housekeeping
  • Experience of working in a project environment delivering data solutions
  • Experience for Retail business needs is an advantage but not essential


Who are we?

We’re one of the UK’s favourite premium chocolate brands, with a range of products spanning luxury gifts, alcohol and our pioneering drinking chocolate system, the Velvetiser™.

We’re market leaders in the industry. What began as an online-only business grew to over 125 stores across the UK, and we’re still growing… Today, we’re multi-category, multi-channel, and multi-territory, and our customers, colleagues, cacao farmers and suppliers all benefit from the success we make together.


As well as a competitive salary and a range of company benefits, you’ll receive50%discount on all products, and a70%discount for you and your guests when you stay at our Rabot Estate hideaway on the paradise island of Saint Lucia.

Here at Hotel Chocolat, we've adopted hybrid working. This means you’ll ideally join us on site for two days a week, and for the other three days - you can work from wherever you like! The on-site location for this role is our support office, ‘Mint House’, in Royston, Hertfordshire. Our home from the very beginning, it’s just off the A505 and 10 minutes’ walk from Royston train station, with direct rail links to London King’s Cross.


If you are interested in this exciting new opportunity, please make an application via our recruitment partner, Datatech Analytics at stating which role you are applying for.

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.

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.

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

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.