Catalyst
Data Engineer (Full-Stack Data Products)

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The Client
Find out exactly what skills, experience, and qualifications you will need to succeed in this role before applying below.
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
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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


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- 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 DevOps 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
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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