At a Glance
- Tasks: Transform raw data into reliable datasets and build scalable data pipelines.
- Company: Join Vanquis, a forward-thinking company focused on data-driven decisions.
- Benefits: Enjoy flexible working, generous leave, and career development opportunities.
- Other info: Collaborate with senior engineers and influence data standards.
- Why this job: Make a real impact by shaping a modern cloud-first data platform.
- Qualifications: Experience in data engineering and cloud environments, especially Azure.
The predicted salary is between 49500 - 60500 £ per year.
Build trusted data products that turn complexity into confident decisions. Vanquis is strengthening how it uses data to improve customer outcomes, insight and competitive advantage. This is an opportunity to help shape a modern, cloud-first data platform at a point when scalable, trustworthy data matters more than ever. As a Data Engineer, you will transform raw information into dependable data products, joining cloud and on-premise sources and making data easier to find, understand and use. Your work will reduce manual effort, improve analyst productivity and support a clearer single source of truth across the business. You will have meaningful ownership without people-management responsibility, working alongside senior data engineering leadership, architects, platform specialists and business partners. It is a hands-on role with the visibility to influence how data engineering standards and practices evolve.
This role is part of a wider Technology & Change journey. Explore our Technology & Change careers page to meet the teams, discover our technology journey and see how you can help shape what's next.
How you’ll make an impact
- Turn complex raw data into trusted, usable datasets so that colleagues can make better-informed decisions using consistent, accessible information.
- Build scalable pipelines for batch and near real-time processing so that data moves reliably across the organisation as demand and complexity grow.
- Connect cloud and on-premise sources to the right data products so that teams gain a clearer, joined-up view without avoidable manual work.
- Strengthen metadata, lineage and data dictionary practices so that data remains searchable, traceable and easier to evidence in a regulated environment.
- Design for performance, testing, automation and secure delivery so that solutions are dependable, maintainable and ready to support critical business needs.
- Shape data marts with engineering, architecture and business partners so that analysts spend less time preparing data and more time creating insight.
- Explore better tools and challenge established approaches so that delivery becomes faster and the platform continues to evolve.
- Share knowledge and document solutions clearly so that the team builds capability and can support what it delivers with confidence.
Why this role matters
Vanquis needs to make better use of its data assets while maintaining the integrity, traceability and controls expected in a regulated organisation. This role helps establish the strong data platform needed to provision information across the organisation, supporting customer outcomes, business insight and future innovation. You will work closely with the Senior Data Engineering Lead, Principal and Lead Data Engineers, the Data Architect, Data Platform and Data Integration teams, as well as Project Managers, Business Analysts, managers and business stakeholders. That breadth gives you a direct view of how well-engineered data improves decisions and day-to-day productivity.
Our Data Engineering approach
- Trusted data: We engineer for quality, lineage and a shared understanding of information.
- Cloud-first thinking: We use modern cloud architecture to create scalable, maintainable data solutions.
- Shared ownership: Engineers, architects, project teams and business partners solve problems together.
- Secure and controlled delivery: GDPR, PCI, risk and good control practices are considered from the outset.
- Continuous improvement: We question existing approaches and adopt tools that improve time to market.
- Learning together: We document well, share experience and help the wider engineering community grow.
Technology stack
- Data platforms & processing: Azure Data Factory, Databricks, Spark, Azure Blob Storage, Azure Data Lake
- Engineering & delivery: Agile, DevOps, CI/CD, test automation, NiFi, Hive, Kafka, HBase
- Metadata-driven pipelines, data modelling, data marts
- Batch and near real-time processing, performance tuning, troubleshooting, secure development
- Cloud and on-premise integration, data lineage, data dictionaries, handover documentation
Essential experience
- End-to-end experience designing and delivering data engineering or analytics solutions in cloud environments, ideally Azure.
- Hands-on experience building high-performing, scalable pipelines for structured and semi-structured data.
- Experience with batch and near real-time processing across multiple sources and targets.
- Practical capability with Azure Data Factory and Databricks or Spark, plus Azure Blob Storage or Azure Data Lake.
- Understanding of data modelling, data marts, metadata-driven development, data dictionaries and lineage.
- Experience delivering through Agile and DevOps practices, including CI/CD, testing and automation.
- Ability to troubleshoot and tune performance while maintaining secure development awareness.
- Confident collaboration with engineers, architects, project teams, analysts and business stakeholders.
- Clear documentation, communication and constructive issue escalation.
- A curious, improvement-focused approach that balances innovation with regulatory and control requirements.
Useful, but not essential
- Experience with NiFi, Hive, Kafka or HBase.
- Experience integrating data across both on-premise and cloud environments.
- Knowledge of data governance in a regulated organisation.
- Awareness of GDPR and PCI considerations in data processing.
Career development
You will deepen your experience across modern Azure data engineering, scalable processing patterns, governance and secure delivery. The role also offers exposure to senior engineers, architecture, platform teams and business stakeholders, with opportunities to influence standards, lead improvements and build towards senior engineering, specialist or future leadership pathways.
Why Vanquis?
- Award-Winning Employer: Great Place to Work Certified, Financial Times Best Employers 2025 & 2026, Armed Forces Friendly Employer, Bronze
- Access to learning resources to support your growth and development
- Flexible Hybrid Working: A balanced approach to office and home working
- Two Volunteering Days: Paid time to support causes that matter to you
- Inclusive Culture: A workplace where colleagues are supported, respected and encouraged to be themselves
- Enhanced Family Leave: Supporting colleagues through important life moments
- Up to 10% Pension Contribution: Helping you plan and prepare for the future
- Paid Birthday Leave: An extra day off to celebrate you
- 25–30 Days Annual Leave: Time away to rest, reset and recharge
- Career Development Opportunities: Support to build skills, grow your career and shape what comes next
Ready to shape what’s next? If you want to build data products that improve decisions, reduce operational effort and help shape a modern cloud-first platform, we'd love to hear from you. The Next Chapter Starts With You.
Recruitment agency information
Our Talent Acquisition team manages all recruitment activity directly. We work with approved recruitment partners where additional support is required. Unsolicited CVs submitted without prior agreement from Vanquis Talent Acquisition will be considered direct applications and no agency fees will be payable.
Data Engineer in Bradford employer: Vanquis
At Vanquis, we pride ourselves on being an award-winning employer that champions quality and innovation in technology. Our inclusive culture fosters collaboration and continuous improvement, providing employees with flexible hybrid working options, extensive career development opportunities, and a supportive environment where everyone can thrive. Join us in shaping the future of technology while enjoying benefits like enhanced family leave, generous annual leave, and dedicated volunteering days.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in Bradford
✨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 Vanquis!
✨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 Vanquis.
✨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 Vanquis.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer at Vanquis, 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 Bradford
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 Vanquis, 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 Vanquis. 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 Vanquis
✨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 Vanquis!
✨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.
