Data Engineer
Vanquis Bradford, England, United Kingdom
Financial Services · 1,001-5,000 employees
About the role
You will transform complex raw data into trusted, usable datasets and build scalable pipelines for batch and near real-time processing. Additionally, you will collaborate with architects and business partners to design data marts and strengthen metadata practices to ensure data traceability.
What they look for
Requirements
Candidates must have end-to-end experience designing and delivering data engineering solutions in cloud environments, preferably Azure. You should also possess hands-on experience with scalable pipelines, data modelling, and Agile/DevOps practices.
Benefits
Full description
THE NEXT CHAPTER STARTS WITH YOU
Data Engineer
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.
There's More to the Story
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
You’ll…
So that…
Turn complex raw data into trusted, usable datasets
Colleagues can make better-informed decisions using consistent, accessible information.
Build scalable pipelines for batch and near real-time processing
Data moves reliably across the organisation as demand and complexity grow.
Connect cloud and on-premise sources to the right data products
Teams gain a clearer, joined-up view without avoidable manual work.
Strengthen metadata, lineage and data dictionary practices
Data remains searchable, traceable and easier to evidence in a regulated environment.
Design for performance, testing, automation and secure delivery
Solutions are dependable, maintainable and ready to support critical business needs.
Shape data marts with engineering, architecture and business partners
Analysts spend less time preparing data and more time creating insight.
Explore better tools and challenge established approaches
Delivery becomes faster and the platform continues to evolve.
Share knowledge and document solutions clearly
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
We believe in
What that means
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
Engineering & delivery
Azure Data Factory • Databricks • Spark • Azure Blob Storage • Azure Data Lake
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?
Benefits & Culture
Learning & Wellbeing
🏆 Award-Winning Employer Great Place to Work Certified • Financial Times Best Employers 2025 & 2026 • Armed Forces Friendly Employer, Bronze
🎓 LinkedIn Learning 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.
#YourVanquis. The Bank that's got your back. For our customers. For our colleagues. For what comes next.
Build your future. Shape ours.
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