Data Engineer (Microsoft Fabric)

Key Responsibilities:This role sits between establishing modern data platform architecture and driving execution for a business-critical BAU acquisition integration programme.Design and embed a scalable, layered Lakehouse data architecture within Microsoft Fabric.Own the automated ingestion, complex transformation, and validation of large incoming financial datasets (transactions, portfolios, and valuations).Drive the adoption of core software engineering disciplines into the data space, including version control and robust CI/CD deployment pipelines.Partner with Middle Office and Finance stakeholders to build optimised semantic models, enabling trusted self-service analytics via Power BI.Establish data quality controls, automated alerting, and clear metadata/data lineage tracking to ensure all reporting remains fully auditable.

Your Background:Experience within Wealth/Asset Management is critical.Deep, hands-on experience building production-grade data pipelines within Microsoft Fabric and Azure ecosystems.Highly proficient in writing performance-tuned SQL and utilising Python for data processing, automation, and testing.While very engineering-focused, having an understanding/background in data analysis will be highly beneficial as you will be working cross-functionally; understanding how front-end users interact with data models.Experience handling financial datasets (investment transactions, portfolio data, operational finance). This is a very dynamic role within a highly successful organisation, with the potential to make a huge impact in this firm's quest to build out its data capabilities.

Wealth Management | 12-Month Contract | £500-600/day

We are partnering with a rapidly expanding, PE-backed Wealth Manager. The business has scaled significantly over the last few years, increasing its AUM following a series of successful acquisitions.Historically, their data environment has been managed by an application development team. They are now separating their data capability to build out a dedicated, specialised data engineering function.