Data Analyst

Reward
Belfast
4 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.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.