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Finance Data Engineer

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Moneycorp Bank Limited
Contract position
Listed on 2026-02-11
Job specializations:
  • IT/Tech
    Data Engineer, Data Analyst, Data Warehousing, Database Administrator
Salary/Wage Range or Industry Benchmark: 80000 - 100000 GBP Yearly GBP 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Location: Greater London

Description

Please note: we are offering this position as a fixed term contract.

Who We Are

Moneycorp powers global payments for corporates, institutions and high net worth individuals, combining worldwide reach with local expertise. With over 45 years of market experience, two banking licences and offices in 11 countries, our technology delivers 24/7 accessibility, while our people deliver award-winning service. In 2024, we supported £79bn+ of international payments, reaching 190 countries in 130 currencies. Our 32k+ corporate clients benefit from our regulatory resilience with 63+ permissions globally, access to major payment rails, and proprietary technology.

Moneycorp is a place where energy, commitment to our shared success, and collaboration are core to our values. We’re restless in our drive to surpass the expectations of our customers and unlock opportunities to support them at every stage of their journey. The foundation of our success is our people, and nurturing a culture of belonging for all our colleagues is central to our journey as a global business.

Who

You Are / Your Next Challenge

The Data Engineer plays a critical role in enabling Finance & Treasury to deliver accurate, timely, and insight‑driven reporting by building scalable data solutions, maintaining core data infrastructure, and supporting the modernisation of Finance systems.

This role is responsible for engineering robust data pipelines, managing datasets across the Microsoft Fabric platform, and ensuring Finance has reliable, consistent, and governed data to support transformation, automation, and improved operational efficiency.

As Finance undergoes significant change, the Data Engineer will be a key technical contributor—helping shape new ways of working, supporting system enhancements, and ensuring Finance is equipped with modern, resilient data capabilities.

Role Responsibilities SQL, Data Extraction and Transformation
  • Design, develop, and maintain SQL data structures within Microsoft Fabric, writing efficient SQL queries and Python‑based transformations to support scalable data pipelines and optimise performance across Lakehouse and Warehouse workloads.
  • Build and maintain reporting datasets optimised for analytics and visualisation, implementing Slowly Changing Dimension (SCD Type
    2) logic to support historical reporting and data accuracy.
  • Ensure data security and integrity throughout the medallion architecture, enforcing access controls, auditing data changes, and ensuring accurate, consistent data is delivered
  • Develop and maintain Power BI semantic models and model layouts built on Microsoft Fabric Gold‑layer datasets, ensuring secure, performant, and well‑governed reporting models for dashboards and analytical consumption.
  • Support the onboarding of new data sources into Microsoft Fabric by working with Dev Ops teams on secure connectivity, API integrations, and operational ingestion processes.
  • Design and develop data pipelines and queries, for efficient data extraction and transformation.
  • Write and maintain production-level code to support lead management and Finance systems, ensuring scalability, performance, and reliability.
  • Development and maintenance of complex datasets needed for reports, dashboards, and visualisations.
  • Troubleshoot database-related issues.
  • Monitor and optimise database performance, identifying and resolving bottlenecks and inefficiencies.
  • Conduct regular reviews of SQL code and queries for performance improvements
  • Ensure data security and integrity.
  • Stay updated with the latest database technologies and best practices.
Data Warehouse
  • Implement best practices for data modelling, ETL processes, and data integration.
  • Optimise data warehouse performance through efficient query design, indexing strategies, and data partitioning.
  • Stay updated on emerging trends and technologies in data management and analytics and evaluate their potential impact on our data warehouse architecture.
Finance System Infrastructure
  • Support configuration changes as needed to meet Finance & Business requirements.
  • Take ownership of upgrade processes including testing and configuration changes, ensuring the current system is fit for purpose…
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