Data Analyst

Reward
Belfast
3 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data analyst

Data Analyst

Data Analyst

Description

You’ll be an enthusiastic database professional with an ability to write and read good-quality SQL code. 

You will work with a multitude of business stakeholders, both technical and non-technical, to scope and build data solutions and exports. This will include database table design, stored procedure design, code review, documentation, progress reports and peer support. You will develop quality assurance (QA) processes and provide a range of regular and ad hoc deliverables to support the business needs and operations. 

You will be able to propose and implement improvements to the existing processes to support the wider business strategy and help shape the future of our data products. 

You’ll have the ability to respond and adapt to a fast-paced working environment and be able to maintain a logical and systematic approach to the solution design of database tasks and projects. 


Key Responsibilities

  • Assess, design, implement and document robust procedures for managing the integrity of data flows 
  • Assist in the development of Reward’s data warehouses to allow access to an ever-growing pool of data in an efficient and scalable manner  
  • Seek practical solutions to reduce time and cost through automation of operational procedures 
  • Carry out systematic data cleansing and enhancement exercises   
  • Undertake regular and ad hoc activities including data provision, report development and exploratory data analysis 
  • Understand and operate the end-to-end campaign selections process, and suggest and implement improvements 
  • Deliver reporting and data extracts to analyse the effectiveness of retailer campaigns 


Skills Knowledge and Expertise

Required 
  • Ability to read and write Structured Query Language (SQL)  
  • Basic understanding of Object orientated languages (preferably Python) 
  • Understanding of logical relational database concepts (e.g. including data types, joins, sub queries, primary and foreign keys, normalisation).  
  • Ability to translate requirements sourced from non-technical clients into effective technical specifications  
  • Ability to produce process documentation that is logically structured and accurate 
  • Experience of working with common data file formats (e.g. csv, fixed width), importing and exporting data, compression, encryption software (e.g. WinZip) and FTP clients. 
  • High attention to detail 
 
Bonus points for any of the following:  
  • Hands on experience of working with a significant size database 
  • Experience of Microsoft SQL Server (2012 or higher) 
  • Experience of Microsoft SQL Server (2012 or higher) Reporting Services and / or Integration Services 
  • Experience of using a BI reporting tool (Tableau, PowerBI, Qlikview) to create dashboards and reports 
  • Experience using a cloud provider (AWS, Google Cloud, Azure) 
  • Advanced knowledge of MS Excel including complex formulae, advanced charting, lookups, PowerPivot and VBA 
  • Business process concepts including, for example, data flows, batch control, validation rules, exception reporting, audit trail and reconciliation 
  • Domain expertise in any of the following: retail, personal banking, direct marketing, digital marketing, CRM, loyalty programmes 
  • Educated to degree level in a quantitative subject 


Benefits

  • Annual Leave: 25 days + bank holidays
  • Ability to buy and sell holiday days as well as the ability to bank days (tenure dependent) 
  • Flexible working options: we are operating a hybrid working model with 3 days a week from the office
  • Pension: Hargreaves Lansdown – 6% matched contribution 
  • Employee share scheme
  • Generous family friendly cover
  • Private healthcare - Bupa 
  • Income protection
  • Critical illness cover
  • Life insurance cover
  • Dental cover
  • Optical cover
  • Yulife app for access to employee wellbeing and discounts 
  • Perks at Work, cashback/discount shopping site
  • Employee referral scheme 
  • Salary sacrifice program which includes cycle to work scheme, electric car scheme and season ticket loans
  • Volunteering program
  • Company events i.e. Christmas party, all-company event and other social/hosted events during the year (we have an active social committee!)
  • Team socials
Our vision is to be a global leader in customer engagement, helping brands to create customers of the future. How do we achieve this? By making everyday spending more rewarding, we make every interaction count, delivering billions in rewards. 

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.