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AI Data Engineer
Job in
Greater London, London, Greater London, W1B, England, UK
Listed on 2026-09-22
Listing for:
ARC IT Recruitment
Full Time
position Listed on 2026-09-22
Job specializations:
-
Software Development
Data Engineering, AI Engineer (Applied/Software)
Job Description & How to Apply Below
Our client, one of the world's largest independent financial services groups, is looking for an AI Data Engineer to join their central Data Platform team.
This is a rare chance to combine deep data engineering expertise with emerging AI and machine learning capability, within a platform team that sits at the heart of the business.
It is a hands-on role where you will help the data platform evolve to support advanced analytics, machine learning, generative AI and agentic AI, all within a robust governance and control framework.
What You'll Do- Design, build and maintain reusable platform capabilities across the business
- Develop scalable, resilient data solutions using modern cloud data engineering practices
- Act as primary SME for AI-ready data and platform AI capabilities
- Define and maintain standards for data products supporting AI, ML, analytics and automation
- Advise delivery teams on architecture, governance and engineering considerations for AI-enabled solutions
- Build reusable design patterns to accelerate delivery while maintaining consistency and control
- Track developments across Microsoft Fabric, ML, generative AI and agentic AI
- Work with platform engineers, federated data teams, AI practitioners and architects org-wide
- 5+ years in cloud-based data engineering, delivering complex enterprise data solutions
- Strong Python and advanced SQL skills, including hands‑on DBT experience
- Deep understanding of ETL/ELT patterns, data modelling, warehousing, lakehouse and data lake architectures
- Experience with Apache Spark and large-scale data processing
- Strong hands‑on experience with Microsoft Fabric; familiarity with Power BI and semantic models
- Good grasp of machine learning concepts and the data requirements behind them
- Understanding of generative AI and agentic AI patterns
- A track record of setting standards and influencing technical direction across engineering, architecture and stakeholder communities
- Experience in large-scale, ideally regulated, enterprise environments
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