At a Glance
- Tasks: Design and build enterprise-scale data solutions on Azure, optimising data pipelines and collaborating with teams.
- Company: Leading specialty finance business transforming data usage across Finance and Claims.
- Benefits: Competitive salary, bonus, pension, hybrid work, and excellent wellbeing support.
- Other info: Join a dynamic team with a focus on modern cloud data and AI initiatives.
- Why this job: Tackle meaningful data challenges and influence real financial decisions in a collaborative environment.
- Qualifications: Experience in data platforms, advanced T-SQL, Azure Data Factory, and strong communication skills.
The predicted salary is between 50000 - 60000 £ per year.
We’re partnering with a leading specialty finance business that’s investing heavily in its data platform to transform how data is used across Finance, Actuarial and Claims — including AI-driven initiatives that are genuinely moving the needle. This is a hands-on data engineering role where you’ll sit at the heart of the organisation’s data strategy, working closely with senior stakeholders while building modern, scalable solutions on Azure and Databricks.
If you enjoy solving complex data problems in a regulated, data-rich environment - this one’s for you.
The Opportunity
You’ll join a growing data team delivering a wide range of business-critical projects, from modernising legacy data warehouses to enabling advanced analytics and AI use cases across the insurance lifecycle. This role blends deep technical ownership with real business influence — ideal for an experienced Data Engineer who wants to see their work directly impact underwriting, claims and financial decision-making.
What You’ll Be Doing
- Designing and building enterprise-scale data solutions on the Microsoft Azure platform
- Developing and optimising data pipelines using ADF / SSIS, Databricks and Python
- Working with large, complex datasets across Finance, Actuarial and Claims domains
- Supporting the migration and optimisation of legacy SQL Server data warehouses into Azure
- Acting as a senior technical voice within the team — guiding standards, best practice and delivery
- Collaborating with internal teams, offshore partners and senior business stakeholders
- Delivering high-quality, well-tested and well-documented solutions in an Agile environment
What They’re Looking For
- Strong experience designing and delivering enterprise data platforms
- Advanced T-SQL skills (performance tuning, complex transformations, stored procedures)
- Hands-on experience with Azure Data Factory, Databricks and Python
- Solid understanding of data warehousing, ETL, dimensional modelling and data governance
- Comfortable working in Agile teams with CI/CD, Git and Azure DevOps
- Insurance or financial services experience strongly preferred (London Market / Lloyd’s a plus)
- Confident communicator who enjoys working directly with non-technical stakeholders
Why This Role?
- Work on genuinely meaningful insurance data problems — not BAU reporting
- Strong backing for modern cloud data and AI initiatives
- High level of ownership and autonomy
- Hybrid working and a mature, collaborative engineering culture
- Excellent benefits covering financial, physical and mental wellbeing
If you’re a senior data engineer looking to apply modern data engineering and AI techniques within a forward-thinking insurance environment — let’s talk.
Data Engineer in Warrington employer: Loop Recruitment
Join a leading specialty finance business in Manchester that prioritises innovation and employee growth, offering a collaborative and mature engineering culture. With a strong focus on modern cloud data initiatives and AI-driven projects, you'll have the opportunity to work on meaningful challenges while enjoying excellent benefits that support your financial, physical, and mental wellbeing. This hybrid role not only allows for flexibility but also empowers you to make a significant impact on the organisation's data strategy and decision-making processes.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in Warrington
✨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 Loop Recruitment!
✨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 Loop Recruitment.
✨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 Loop Recruitment.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer at Loop Recruitment, 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 in Warrington
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 Loop Recruitment, 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 Loop Recruitment. 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 Loop Recruitment
✨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 Loop Recruitment!
✨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.
