At a Glance
- Tasks: Build and maintain data pipelines, ensuring reliable data flows and quality assurance.
- Company: Join Quantum, a leading digital comparison service driving growth through data-driven marketing.
- Benefits: Enjoy private health care, hybrid working, competitive salary, and regular team events.
- Other info: Dynamic team culture with opportunities for professional growth and recognition.
- Why this job: Make a real impact in a fast-paced environment while learning cutting-edge data engineering skills.
- Qualifications: Bachelor's degree in a related field and some coding experience, preferably in Python or SQL.
The predicted salary is between 50000 - 70000 £ per year.
Our Company At Quantum, we connect global brands with high-intent consumers. We turn intent into action and complexity into clarity. Our Mission is clear, to help smarter, faster buying decisions. Our vision, to be the world’s most used digital comparison service, delivering value and simplicity to millions. We drive growth through data-driven affiliate marketing built for performance from day one. Every campaign is measurable, optimised in real time, and designed to scale. With in-house tech, full-stack analytics, and a compliance-first mindset, we give our partners an edge. We drive confident decisions and growth in regulated and high-growth sectors. We’ve helped ambitious brands grow faster, smarter, and globally.
The Role As a Data Engineering Graduate, you'll be an integral part of our Data Engineering team. From day one, you'll gain hands‑on experience, taking on meaningful responsibility, and making a tangible impact. This role is ideal for someone who likes building things that last and wants to learn how reliable data infrastructure is designed, built and maintained at scale.
Key Responsibilities
- Pipeline development: you'll help build and maintain the data pipelines that ingest, clean and move data across our systems, learning how reliable data flows are engineered.
- Data integration: you'll support the onboarding of new data sources, writing and testing the logic that brings partner data into our platform cleanly and consistently.
- Transformation and modelling: you'll apply transformations that turn raw data into structured, trustworthy datasets the wider business can use.
- Monitoring and reliability: you'll help keep our ingestion pipelines running, flagging issues early and learning how we maintain the integrity of our data operations.
- Quality assurance: whether it's checking for anomalies or validating schemas and formats, your attention to detail will keep our data trustworthy and actionable.
- Automation and process improvement: you'll help identify and implement ways to streamline and scale our data processes, bringing more automation, speed and accuracy to the team.
- Documentation: you'll capture and update data rules, pipeline logic and key processes to support operational clarity and team knowledge sharing.
You'll use your natural curiosity to stay up to date with engineering practices and tools, contributing fresh ideas to the team.
About You
- Bachelor's degree in computer science, software engineering, data science, mathematics, or a related field (or similar qualification).
- Some exposure to coding, ideally Python or SQL, through your studies, projects or self‑teaching, with a genuine eagerness to deepen it.
- A keen eye for detail and a passion for getting data right, because small errors can make a big difference downstream.
- Comfortable picking up new tools, platforms and technical concepts quickly.
- Proactive and inquisitive, happy to ask questions and figure things out.
- Organised and methodical in how you approach tasks and documentation.
- You thrive when working as part of a team.
- Comfortable in a fast‑paced environment.
- Have excellent written and verbal English skills.
- Last but not least, you'll have no ego!
What You’ll Get
- Private Health Care (Bupa).
- Hybrid Working (3 days in office).
- Travel Insurance.
- Competitive Base Salary.
- Company Bonus Scheme.
- Paid for AI Subscription (Claude / ChatGPT / Gemini).
- Market‑Leading Training Programme.
- Recognition & Reward Scheme.
- Annual Company Conference.
- Regular Happy Hours & Team Lunches.
- Free Coffee, Drinks & Snacks.
What’s the next step?
Our hiring process ensures we're recruiting the right people for the role. We ensure that people are as suitable for us as we are for them. If you like the sound of what we're all about at Quantum and want to join a team where you can make an impact, please apply or contact us at careers@quantum.media.
Graduate Data Engineer employer: Quantum
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StudySmarter Expert Advice🤫
We think this is how you could land Graduate 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 Quantum!
✨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 Graduate Data Engineer at Quantum.
✨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 Quantum.
✨Apply Directly through Our Website
When you find a suitable opening like Graduate Data Engineer at Quantum, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Graduate 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 Quantum, 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 Quantum. 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 Quantum
✨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 Quantum!
✨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.
