Graduate Cloud Engineer – The Mobilise Academy 2027 Cohort
Hybrid in Bridgend +1
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168,000+ live jobsHybrid in Winchester·Added today (last checked 26 Oct)
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We're looking for a Data Engineer who enjoys working across the whole stack: building reliable data pipelines, putting AI and machine learning into production, and writing solid software to tie it all together.
This isn't a narrow, single-lane role. You'll move between data, AI and engineering work depending on what the team needs most, and you'll be comfortable picking up new tools as our platform evolves.
Design, build and maintain scalable data pipelines (batch and streaming) that feed analytics, reporting and AI workloads
Model, clean and organise data so it's reliable, well documented and easy for others to use
Look after data quality, monitoring and governance across the platform
Prepare and manage the data that powers machine learning models and AI features
Help integrate AI technologies, such as large language models, retrieval-augmented generation (RAG) and ML services, into our products and workflows
Support the deployment, monitoring and improvement of models in production
Keep an eye on the fast-moving AI landscape and suggest where new tools could add value
Write clean, tested, maintainable code, mainly in Python and Java
Build services, APIs and tooling that connect data and AI components to the wider system
Contribute to code reviews, CI/CD pipelines and good engineering practice across the team
Work with analysts, data scientists, engineers and business stakeholders to turn problems into practical solutions
Pick up whatever needs doing to move work forward, from infrastructure to documentation
Proven experience in a data engineering, software engineering or similar technical role
Strong programming skills in at least one general-purpose language, ideally Python or Java, and willingness to work in both
Solid SQL and a good grasp of data modelling, ETL/ELT and pipeline design
Hands-on experience with at least one major cloud platform (e.g. AWS, Azure or GCP)
Practical exposure to AI or machine learning, whether building models, integrating AI services or preparing data for them
Familiarity with software engineering fundamentals: version control, testing, code review and CI/CD
The ability to explain technical ideas clearly to both technical and non-technical colleagues
You must have been resident in the UK for at least the last five years. Successful candidates will need to obtain and maintain this clearance as a condition of employment.
Experience with distributed data processing or streaming tools (e.g. Spark, Kafka)
Workflow orchestration (e.g. Airflow, Dagster or similar)
Working with LLMs, vector databases, embeddings or RAG patterns
MLOps practices: model versioning, deployment and monitoring
Containers and infrastructure as code (e.g. Docker, Kubernetes, Terraform)
Experience with modern data warehouses or lakehouses (e.g. Snowflake, Databricks, BigQuery)
We care more about range and attitude than ticking every box. You'll do well in this role if you:
Enjoy variety and are happy to switch between data, AI and software work as priorities change
Are curious and pick up new languages, tools and frameworks quickly
Take ownership of problems end to end, rather than handing off at the edge of your specialism
Prefer practical, working solutions over perfect ones, and know when to go deeper
Share knowledge openly and enjoy helping the people around you improve
If you don't meet every requirement but this sounds like you, we'd still encourage you to apply.
A competitive salary.
A clear path for career development and certification support (AWS, Azure, Terraform).
Hybrid working model (50% home, 50% office in Winchester).
Company pension scheme.
25 days annual leave plus public holidays.
MediCash, Cycle to Work, EV Scheme
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