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Data Engineer

Job in Bradford, Franklin County, Iowa, 50041, USA
Listing for: Vanquis
Full Time position
Listed on 2026-09-13
Job specializations:
  • IT/Tech
    Data Engineering
Salary/Wage Range or Industry Benchmark: 94658.9 - 128465 USD Yearly USD 94658.90 128465.00 YEAR
Job Description & How to Apply Below

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…

  • Turn complex raw data into trusted, usable datasets
  • Build scalable pipelines for batch and near real‑time processing
  • Connect cloud and on‑premise sources to the right data products
  • Strengthen metadata, lineage and data dictionary practices
  • Design for performance, testing, automation and secure delivery
  • Shape data marts with engineering, architecture and business partners
  • Explore better tools and challenge established approaches
  • Share knowledge and document solutions clearly
So that…
  • Colleagues can make better‑informed decisions using consistent, accessible information.
  • Data moves reliably across the organisation as demand and complexity grow.
  • Teams gain a clearer, joined‑up view without avoidable manual work.
  • Data remains searchable, traceable and easier to evidence in a regulated environment.
  • Solutions are dependable, maintainable and ready to support critical business needs.
  • Analysts spend less time preparing data and more time creating insight.
  • Delivery becomes faster and the platform continues to evolve.
  • 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

NiFi, Hive, Kafka, HBase

Batch and near real‑time…

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