This role sits within the Operational Excellence Hubs (OEH). OEH is an innovative, agile and collaborative function that provides services to support our client-facing colleagues in the delivery of their work. OEH supports the business through a variety of specialist teams, who work collaboratively to support the business to run smoothly.

The Credit Management department is part of OEH Finance. You will be joining a team that provides vital credit control support to the Business, working with a wide portfolio of blue-chip companies, providing high level credit control administration and support, delivering excellent customer service on a variety of tasks and activities and enabling customers to focus on their core business objectives contributing to KPMG’s goal of driving growth through operational excellence.

KPMG is creating a new "best in class" Testing Practice with a clear mission - to accelerate business change. By leveraging KPMG's considerable in-house industry knowledge with the leading test tools, methods and practices, KPMG is seeking to help our clients deliver efficient, high-quality change – while minimising risk.

We are currently recruiting Principal Advisors who can make a significant contribution to the creation and development of KPMG’s Testing Practice within the Management Consulting Technology Enablement team, through sector expertise, client engagement and delivery of new business opportunities.

Our Contract Performance & Insight (CP&I) team sits within KPMG’s Customer and Operations Advisory practice. We’re a dynamic mix of qualified accountants and commercially minded professionals who help clients unlock value from their third-party contracts.

Using a blend of audit techniques, technology, and strategic thinking, we analyse financial performance and contract compliance to identify cost recovery opportunities and drive operational improvements. Our work spans a wide range of agreement types—from royalties and software to supplier contracts—across both public and private sectors.

KPMG’s Cloud Transformation practice is an award-winning team of over 50 consultants that helps clients transform the way CIOs and their teams deliver technology services to their business stakeholders. Our team help the UK’s largest and most complex organisations develop cloud strategies, build the operating models, architectures and capabilities to deliver value from cloud, and operate their cloud or hybrid estates effectively and cost-efficiently.

To support our clients, we use KPMG’s deep industry insights, C-suite relationships, cloud architecture capabilities, alliances and accelerators ranging from our cloud value labs, KPMG Cloud Cost Management models, Cloud controls frameworks and landing zones.  Our 350+ strong engineering teams implement these strategies and solutions – sitting at the heart of major transformations across the UK, helping technology executives convert business strategy into compelling technology outcomes.

We are looking for a skilled and proactive Data Engineer with strong expertise in the Microsoft Azure data ecosystem, including Microsoft Fabric, Synapse Analytics, and Delta Lake. This role requires hands-on experience in building and optimising data pipelines and notebooks, transforming large datasets, and enabling data-driven decision-making across the organisation.

The successful candidate will play a key role in designing and implementing scalable data solutions, collaborating with both technical and non-technical stakeholders, and helping shape our modern data architecture.

Key Responsibilities

• Design, develop, and maintain robust data pipelines and notebooks using Synapse Analytics and Microsoft Fabric.
• Build and optimise complex data transformation and ingestion logic to support enterprise-level reporting and analytics.
• Leverage Delta Lake architecture to support both batch and streaming data processes.
• Develop high-quality, reusable code in Python and PySpark, following best practices and ensuring maintainability.
• Create insightful, interactive reports and dashboards using Power BI.
• Use Git and Azure DevOps (ADO) for version control and deployment workflows.
• Continuously improve the performance, reliability, and scalability of data systems.
• Advocate for best practices in data governance, data quality, and documentation.