At a Glance
- Tasks: Design and build cutting-edge data platforms for analytics and AI.
- Company: Join a forward-thinking company at the forefront of cloud technology.
- Benefits: Enjoy enhanced leave, sick pay, and personalised development plans.
- Other info: Be part of a dynamic team with excellent career growth opportunities.
- Why this job: Shape the future of data and AI while influencing key business decisions.
- Qualifications: Proven experience in data engineering and strong cloud platform skills.
The predicted salary is between 72000 - 88000 £ per year.
Our client are seeking an experienced Senior Data Engineer to play a pivotal role in designing and building the data platform that will power the organisation's next generation of analytics and AI capabilities.
This is a hands‑on leadership role where you will take ownership of how data is structured, governed, and leveraged across the business.
You will be responsible for defining the strategic direction of the data platform while actively contributing to its design, development, and implementation.
Working closely with senior stakeholders, including the CTO, you will help shape the organisation's data and AI strategy, enabling everything from enterprise reporting and advanced analytics to cutting‑edge AI and machine learning solutions.
Responsibilities
- Design and build scalable, cloud-based data platforms and architectures.
- Translate business requirements into robust, scalable data solutions.
- Develop conceptual, logical, and physical data models.
- Design and implement modern AI-ready architectures, including RAG, vector databases, semantic search, and LLM integrations.
- Build and optimise data pipelines supporting both batch and real-time processing.
- Lead data integration, transformation, and migration initiatives.
- Establish and maintain data governance, data quality, metadata management, and security frameworks.
- Collaborate with engineering, architecture, and business stakeholders to deliver impactful solutions.
- Evaluate emerging technologies and recommend innovative approaches to enhance data and AI capabilities.
- Provide technical leadership, best practice guidance, and mentoring across data initiatives.
- Ensure data platforms are scalable, secure, cost-effective, and aligned to business objectives.
- Define the organisation's data and AI strategy from the ground up.
- Work directly with senior leadership and influence business-critical decisions.
- Build solutions using the latest cloud, data, and AI technologies.
- Drive architectural decisions and implement best practices.
- Access tailored development plans, training, and certification support.
- Join a business actively investing in transformation and AI adoption.
Benefits
- Enhanced annual leave plus birthday leave
- Enhanced sick pay
- Enhanced maternity benefits
- Personalised development plans
- Structured training and development programmes
- Paid social events
- Cycle to Work scheme
As part of Cloud Bridge, an AWS Premier Partner, we bring deep cloud expertise into every hiring conversation.
Here, technology meets empathy - connecting the dots between ground-breaking companies and exceptional talent.
Essential
- Proven experience in a senior Data Engineering, Data Architecture, or Lead Data role.
- Strong hands‑on experience designing and delivering cloud-based data platforms.
• Expertise with one or more of the following technologies
- AWS (Redshift, Glue, S3, Bedrock)
- Microsoft Azure (Synapse, Data Factory, Azure SQL)
- Databricks (Delta Lake, ETL pipelines, ML workloads)
- Snowflake
- Strong data modelling experience across enterprise-scale environments.
- Experience building modern AI-enabled data architectures.
- Knowledge of Retrieval-Augmented Generation (RAG), vector databases, embeddings, and LLM integrations.
- Experience with both batch and streaming/real-time data processing.
- Strong understanding of data governance, quality management, lineage, and metadata frameworks.
- Excellent stakeholder engagement and communication skills with the ability to translate complex technical concepts into business outcomes.
Desirable
- Experience within Financial Services, Professional Services, or Advisory environments.
- Knowledge of Fin Ops, cloud cost optimisation, and total cost of ownership considerations.
- Relevant cloud and data certifications.
- Exposure to MLOps and AI platform engineering.
- #J-18808-Ljbffr
Data Engineer employer: Cloud Bridge
Join a forward-thinking organisation in Newcastle Upon Tyne as a Senior Data Engineer, where you will have the opportunity to shape the future of data and AI strategy. With a strong emphasis on employee growth, the company offers tailored development plans, structured training programmes, and a vibrant work culture that encourages innovation and collaboration. Enjoy competitive benefits including enhanced annual leave, sick pay, and maternity benefits, all while working in a dynamic environment that values your contributions and fosters professional advancement.
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 Cloud Bridge!
✨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 Cloud Bridge.
✨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 Cloud Bridge.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer at Cloud Bridge, 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
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 Cloud Bridge, 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 Cloud Bridge. 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 Cloud Bridge
✨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 Cloud Bridge!
✨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.
