At a Glance
- Tasks: Build AI solutions that enhance productivity and decision-making across the business.
- Company: Join Currys, the UK's leading tech retailer with a passion for amazing technology.
- Benefits: Hybrid working, ongoing training, and opportunities for career growth.
- Other info: Collaborative culture focused on inclusion and diversity.
- Why this job: Be a change agent in a fast-paced environment and make a real impact.
- Qualifications: Experience in Python, APIs, and a genuine interest in AI and ML.
The predicted salary is between 30000 - 40000 £ per year.
At Currys we’re united by one passion: to help everyone enjoy amazing technology. As the UK’s best-known retailer of tech, we’re proud of the service our customers receive – and it’s all down to our team of 25,000 caring and committed colleagues. Working as one team, we learn and grow together, celebrating the big and small moments that make every day amazing.
Currys is in the middle of one of the most ambitious AI and automation shifts in UK retail. We are rethinking how customers discover and buy technology, how stores operate, how supply chains move, and how colleagues do their best work. We’re reshaping how the business trades, plans and serves. The AI & Monetisation function is where the boldest bets get placed. The squad you join is greenfield, built around a real business domain, and backed by senior sponsorship. You will own that domain end to end, set the roadmap with the stakeholders who run it, and ship products that move the numbers in the P&L.
These problems are genuinely hard: optimising stock availability, automating complex operating processes, putting useful AI into the hands of frontline colleagues, and monetising the audience and data we already have. You will be a change agent in a business moving fast and willing to back people who can move with it.
Role overview
All the amazing things you'll do:
- Build AI solutions and agents that improve productivity and decision‑making across the business.
- Create and iterate on prototypes using modern LLM and agent frameworks.
- Help take AI features into production, working with senior engineers to meet reliability and security needs.
- Contribute to data preparation and feature engineering for AI use cases.
- Write clean, well‑tested code that follows Currys engineering standards.
- Monitor AI solutions in production, tracking quality, performance and cost.
- Troubleshoot issues and improve implementations based on feedback and metrics.
- Document your work clearly so solutions can be supported and scaled by the wider team.
- Learn continuously and bring new ideas, tools and techniques to the team.
All the things you'll bring:
- Strong engineering foundations with real experience delivering working solutions in a team.
- Comfortable with Python and the ability to write code that others can understand and maintain.
- Practical knowledge of APIs, services and development practices like version control, code reviews and testing.
- Evidence you've already started building with AI - through personal projects, a starter role, or experimenting with tools like Codex or Cursor.
- Understanding of basic ML and AI concepts like prompting, evaluation, embeddings and how models work.
- Intellectual curiosity and problem‑solving instincts that drive you to figure things out.
- A genuine desire to learn fast and grow your skills in applied AI and agentic tooling.
- The ability to work collaboratively in an agile environment with product teams and multiple stakeholders.
- Exposure to Databricks, Azure AI services or similar cloud AI platforms beneficial.
- Experience with agent frameworks, RAG patterns or orchestration tools beneficial.
- Knowledge of data platforms like SQL or Spark and how AI integrates with them beneficial.
The essentials:
- Engineering experience in software, data or ML with real‑world delivery in a team setting.
- Working proficiency in Python and writing production‑quality code.
- Familiarity with APIs, services and modern development practices like version control and testing.
- Early evidence of AI or LLM work through personal projects, a starter AI role, or building tools using Codex, Cursor, OpenAI APIs or similar.
- Degree in Computer Science, Engineering, AI/ML, or equivalent experience.
Join our team and we'll be with you every step of the way, helping you develop the career you want with new opportunities, on‑going training and skills for life. Not only can you shape your own future, but you can help take charge of ours too. As the biggest recycler and repairer of tech in the UK, we’re in a position to make a real impact on people and the planet. Every voice has a space at our table and we're committed to making inclusion and diversity part of everything we do, including how we strengthen our workforce.
We want to make sure you have a fair opportunity to show us your talents during our application process, so if you need any additional assistance with your application please email careers@currys.co.uk and we'll do our best to help.
Data Engineer employer: Currys
At Currys, we pride ourselves on being a leading tech retailer that fosters a collaborative and inclusive work environment. Our commitment to employee growth is evident through ongoing training and development opportunities, allowing you to shape your career while contributing to innovative AI solutions that impact the retail landscape. With a focus on sustainability and diversity, working in our Waterloo office means being part of a team that values every voice and strives to make a positive difference in both the business and the community.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Currys!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer at Currys.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Currys.
✨Apply Directly through Our Website
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We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Currys, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Currys. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Currys
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Currys!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
