At a Glance
- Tasks: Design and maintain data pipelines, ensuring quality and reliability for analytics and AI applications.
- Company: Join Quantium, a global leader in data science and AI with a collaborative culture.
- Benefits: Enjoy flexible work arrangements, private medical insurance, and opportunities for career growth.
- Other info: Connect with diverse colleagues and explore various roles within the company.
- Why this job: Make a real impact while developing your skills in a fast-paced, innovative environment.
- Qualifications: 1-2 years of experience in data engineering or relevant academic projects; Python and SQL skills required.
The predicted salary is between 30000 - 40000 £ per year.
Who is Quantium?
Quantium is a world leader in data science and artificial intelligence. Established in Australia in 2002, Quantium is a global team of more than 1,200 people across 14 locations with a unique blend of capabilities across product and consulting services to help businesses unlock value from data and analytics. Quantium partners with the world’s largest corporations to forge a better, more intelligent world.
Our Technology & Delivery team builds the engineering foundations that make analytics and AI‑driven decision making possible – from robust data pipelines to cloud‑native platforms deployed for some of the UK’s most prominent organisations. We are looking for a curious and motivated Data Engineer to join our growing team in Manchester. This is an excellent opportunity for someone early in their engineering career who is passionate about data and eager to develop their skills in a fast‑paced, commercially driven environment. Working alongside experienced engineers, consultants and analysts, you will gain hands‑on exposure to modern data engineering practices across cloud platforms and a range of real‑world client challenges.
Responsibilities
- Pipeline development: Design, build and maintain data pipelines that ingest, transform and deliver data across client environments, contributing to the engineering foundations that power analytics and AI applications.
- Data architecture: Contribute to the design and documentation of data models, schemas and architecture decisions that ensure data is well‑structured, accessible and ready to support intelligent systems.
- Quality and reliability: Participate in code reviews, support pipeline monitoring and proactively elevate issues – helping the team deliver consistently high‑quality outputs for our clients.
- Collaborative working: Partner with data scientists, analysts and consulting teams to understand requirements and deliver against agreed outcomes, contributing actively to Agile ceremonies.
Qualifications
- Technical foundation: Around 1–2 years of commercial experience in data engineering or a closely related discipline, or equivalent demonstrated through academic projects or internships.
- Python and SQL: Exposure to Python and SQL and ability to write clean, well‑tested code in a production context.
- Data concepts: Foundational understanding of databases, data structures, data flows and transformation logic.
- Cloud awareness: Some exposure to cloud platforms (AWS, Azure or GCP), or the eagerness to develop this knowledge quickly.
- Engineering practices: Awareness of version control using Git and a willingness to engage with software development best practices.
- Problem solver: Strong attention to detail and a natural curiosity for working through technical challenges.
- Collaborator: Effective communicator who can work well within a team, including with non‑technical stakeholders.
- Academic background: Degree in Computer Science, Engineering, Mathematics, Statistics or a related field.
- AI exposure: Experience with modern AI and machine learning concepts, including large language models (LLMs) or agentic systems, is advantageous.
Benefits and Growth Opportunities
- Forge your path: Many team members move across roles or offices; you will have the freedom to shape your career.
- Find your kind: Embrace diversity and connect with colleagues who share interests such as food, dogs, books or running.
- Make an impact: Your contributions resonate regardless of your role or rank.
- Private medical insurance: Convenient access to medical treatments.
- Flexible work arrangements: Achieve work‑life balance with hybrid and flexible working options.
- Remote working: Opportunity to work outside your assigned home location for up to one month per year.
Data Engineer in Manchester employer: Quantium South Africa
At Quantium, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of Leeds. Our commitment to employee growth is evident through tailored development programmes and opportunities to lead transformative projects in the retail sector, ensuring that our team members not only contribute to impactful initiatives but also advance their careers in a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in Manchester
✨Embrace Online Competitions
Get involved in online data science competitions like Kaggle or DrivenData. These platforms not only let you showcase your skills but also help you build a portfolio that stands out to hiring companies like Quantium South Africa when you're aiming for that entry-level role.
✨Join Data Science Meetups
Look for local data science meetups or workshops happening in your area. These are perfect for connecting with industry professionals and fellow newbies, giving us the chance to learn the ropes and get our foot in the door at companies like Quantium South Africa.
✨Networking Through University Career Services
Don't forget to leverage your university's career services! They often have exclusive internships and networking events specifically for entry-level data science positions. This is a golden opportunity to meet recruiters from companies like Quantium South Africa.
✨Spotlight Your Skills Online
Create a strong online presence by sharing your projects and insights on platforms like GitHub or LinkedIn. Make sure to apply directly through Quantium South Africa’s career page, where your unique skills can shine in their entry-level data science openings!
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at Quantium South Africa, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at Quantium South Africa aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
Show Your Curiosity:In the data science world, curiosity is key! Mention any online courses or certifications you've pursued that complement your studies. This could be anything from a statistics certification to a data visualisation workshop. It shows us you're serious about learning and growing in this field.
How to prepare for a job interview at Quantium South Africa
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
