Data Engineer

Gregory Group
Cullompton
5 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Cullompton

(with Hybrid Working)

As a result of continued growth, we have a vacancy for aData Engineerto join the Gregory Group Technology Team. This is an exciting opportunity to make your own within the Gregory Group. 

The position of Data Engineer involves:

Creating and maintaining database schemas for use in our data warehouse, in-house applications and integrations. Creating and maintaining existing and new ETL processes using SQL Stored Procedures and Azure Data Factory. Contributing to the design, maintenance and development of a high quality, robust and performant centralised data source comprising data from multiple business systems, both cloud-based and on-premise – which supports business intelligence and analysis development. Managing, monitoring and optimising both on-premises and Azure SQL servers including indexing, maintenance plans and query / performance optimisation. Automating data retention policies and other housekeeping activities to optimise performance and meet compliance requirements. Designing and delivering business intelligence and reporting solutions using both traditional (MS SQL, SSRS) and modern (BI) tools, technologies and methods. Continuous improvement of data schemas, reports, dashboards and business intelligence solutions. Maintaining accurate documentation of solutions and supporting cross-skilling across the wider Data Services team. Delivering customer-specific requirements as part of an implementation / onboarding project or as part of business-as-usual. Understanding our people and processes as well as business problems and opportunities and using this contextual knowledge to translate business requirements into technical solutions tailored and appropriate for the audience. Consulting as part of project processes to define data, reporting and BI requirements, suggesting enhancements as appropriate. Highlighting opportunities based on your understanding of the business and knowledge of our data for where data, analytics or BI solutions can help to improve business performance. Working with the wider Group Technology team to ensure smooth running of systems and relevant dependent services such as integration and application development. This will include working with our infrastructure and security team to ensure data systems are secure and performant. Working closely with our PMO function and assigned Project Manager’s, updating on task progress and escalating risks or dependencies where necessary. Using our project and task management tool, JIRA, ensuring that tasks as prioritised and kept up to date for visibility across the team and PMO.

Essentials Skills required for aData Engineer:

Minimum of 3 years’ experience in a similar data engineering / development type role. Experience of Azure Data Factory or other similar cloud-based modern data tools. High aptitude for data schema and ETL design and confident working with data. High degree of proficiency with MS SQL, SSRS. Experience of using Power BI or other similar BI tool desirable. Experience of using modern cloud data platforms desirable. Highly motivated with a curiosity to understand business process and problems to identify opportunities. Critical thinking and analytical mindset to problem solving. Excellent written and verbal communication skills. Full UK driving licence as occasional travel between Gregory Group locations may be required.

Why Gregory Distribution?

Salary for Data Engineer is from £43,pa - £48,pa, dependant on experienceHours of work are Monday to Friday 08:30hrs to 17:00hrs.Opportunity to develop your career within an expanding business.Additional holiday purchasing scheme*Retail discounts with Hapi*Retail Trust Wellbeing Support*Opportunity to develop your career within an expanding business.Excellent holiday allowance and company benefits.Life assurance, pension and sickness scheme*Christmas Savings Club*Black Circle Tyre discount*Leading industry qualifications*Medical Reimbursement*This vacancy is not entitled to the employee referral scheme.Free Uniform.Strong culture of teamwork.

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.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.