At a Glance
- Tasks: Develop and maintain scalable data systems and pipelines for analytics and AI-driven products.
- Company: Join a prestigious tech consulting firm in Newcastle with a collaborative culture.
- Benefits: Competitive salary, growth opportunities, and a dynamic work environment.
- Other info: Exciting chance to grow in a rapidly expanding business.
- Why this job: Be part of an elite team driving innovation in data engineering.
- Qualifications: Strong Python and SQL skills, with experience in data engineering and cloud platforms.
The predicted salary is between 60000 - 80000 £ per year.
The Client
We are delighted to be , once more, recruiting on behalf of our prestigious client, a newly created JV Technology Consulting business formed by global leaders in the fields of management consulting and investment fund management.
Based in Newcastle upon Tyne at their enviable facilities, my client seek a Data Engineer for Full-Stack Data Products, to join their elite Tyneside team as part of rapid expansion of the business to cope with client demand and continued excellent performance.
About the Role
As a Data Engineer you will play a key role in developing, building and maintaining scalable data intensive systems, pipelines and platforms that power analytics, operational systems, and AI-driven products.
This role combines full-stack or backend software engineering with modern data engineering, requiring someone with a broad skillset and who excels in solving problems across application development, data pipelines, cloud infrastructure, and platform automation.
Key responsibilities include
- Software Design: Develop, and maintain production-grade applications and APIs.
- Application Build: Develop reusable, well-tested code following engineering best practices.
- Architecture: Participate in architecture and technical design discussions.
- Testing: Write automated unit, integration, and end-to-end tests.
- Data Pipeline Development: Design and develop sophisticated data pipelines to import data from internal and external sources and seamlessly integrate into data platforms.
- Maintenance & Data
Reliability: Ensure systems are well-maintained, enabling uninterrupted access to crucial data.
Continuously verify data quality and integrity to support decision making.
- Continuous Improvement & Collaboration: Collaborate with internal and external stakeholders to streamline data accessibility and usability.
Drive innovation by adopting advanced analytics technologies and methodologies.
- Cloud infrastructure: Deploy cloud-native solutions using Infrastructure as Code and collaborate on cloud architecture and optimisation
About You
To be considered for the role, it is essential that you possess exemplary academic prowess, with a 2:1 or 1st in a relevant subject (e. g.
Computing Science, Maths, Physics etc.) from a leading University and accompanying demonstrable experience gained working as a Data Engineering professional.
It would be highly advantageous if you possessed experience working in the Financial Services Sector.
- Key Selection Criteria
- Expertise in designing and building data intensive applications and pipelines, with an open mindset on choice of tools
- Strong proficiency in Python and SQL, with a focus on writing clean, performant code to process and manage large volumes of data
- Experience designing and implementing complex data-matching, reconciliation, and entity-resolution solutions across multiple data sources
- Distributed computing for data intensive work such as Spark and Databricks
- Cloud platforms including AWS, Azure and GCP
- Orchestration tools like Airflow
- Modern Dev Ops practices including version control, CI/CD, and infrastructure as code using Terraform or Kubernetes
- Experience building scalable backend applications
- Understanding of distributed systems and software architecture.
- Ability to test and troubleshoot data products with a track record of improving data reliability and quality
- Excellent communication skills and the ability to work effectively and openly within a team-based environment
- Self-motivated, detail-oriented, and eager to learn new technologies and methodologies
This is an excellent opportunity to join a leading business that only employs exceptional, collaborative and passionate people.
This rapid expansion phase is the ideal time to be joining such a prestigious business
Data Engineer (Full-Stack Data Products) in Newcastle upon Tyne employer: Catalyst
As a leading international technology manufacturer based in County Durham, our company is committed to fostering a dynamic and inclusive work environment where innovation thrives. We offer competitive benefits, a strong focus on employee development, and the opportunity to lead high-impact projects in a collaborative setting. Join us to be part of a culture that values accountability, continuous improvement, and cross-site collaboration, ensuring your contributions are recognised and rewarded.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (Full-Stack Data Products) in Newcastle upon Tyne
✨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 Catalyst!
✨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 (Full-Stack Data Products) at Catalyst.
✨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 Catalyst.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer (Full-Stack Data Products) at Catalyst, 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 Data Engineer (Full-Stack Data Products) in Newcastle upon Tyne
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 Catalyst, 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 Catalyst. 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 Catalyst
✨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 Catalyst!
✨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.
