NatWest Rooster Money: Delivering Modern Data Transformation at Pace
the challenge
How NatWest Rooster Money is simplifying, modernising and making its data estate more accessible – and showing what modern data delivery at pace can look like in practice
Introduction
NatWest Rooster Money exists to make it easy for parents to give every child the best start with money.
That mission is simple but powerful. It gives NatWest Group an earlier connection with young customers and their families, creating a meaningful opportunity to build money confidence from the very start of the customer journey.
Since becoming part of the Group in 2021, NatWest Rooster Money has grown rapidly – scaling by more than 15x to ~600K. That growth made the next challenge clear: the data environment needed to scale with the business, support stronger connectivity across the Group, and do so without losing pace.
This was a significant data transformation spanning architecture, platforms, governance, reporting, integration and ways of working — all while the business continued to scale and demand from across the Group increased. It needed to move quickly, without compromising the controls expected within a NatWest Group environment.
The challenge: Bank-grade controls, fintech-speed execution
As part of the Group, NatWest Rooster Money needed to retain the pace and customer focus of a fast-moving digital proposition while meeting growing expectations around governance, regulatory reporting and Group connectivity.
As the business scaled, the data estate evolved to meet immediate needs. Over time, this created multiple architectures, duplicated effort and siloed connectivity. The same data was being transformed, governed and made available in different ways across different platforms and journeys.
This created three connected challenges:
- Scaling became less efficient for a small, highly focused data team
- Applying governance and controls consistently became harder as complexity increased
- Making NatWest Rooster Money data accessible and reusable across the wider Group was more difficult than it needed to be
The task was not simply to modernise, but to simplify a complex, live estate while continuing to deliver.
The scale: why this was a big piece of work
This was not a small reporting tidy-up or a single-platform migration.
The data estate includes hundreds of terabytes held in the data lake, significant daily data ingestion, approximately 17 data sources, and a codebase of more than 100,000 lines spread across three data architectures. Another way to think about it is as a live industrial production line: a huge volume of new material arrives every day from 17 different suppliers, moves through three different factories, and still has to meet high standards of quality and control throughout.
For a focused team, that meant maintaining multiple platforms, pipelines and control models in parallel while continuing to deliver for the business.
Simplification was not cosmetic. It was essential to reduce duplication, manage risk and protect the team’s ability to keep delivering as the business continued to grow.
What makes this work notable is that NatWest Rooster Money took on enterprise-level data complexity while maintaining the pace and pragmatism of a fintech — something that is difficult to sustain at this scale within a regulated Group environment.
data services
the solution
The solution: simplify, standardise and make data more accessible
Rather than continuing to evolve multiple architectures in parallel, the team made a deliberate decision to reduce duplication and standardise how data was managed, governed and shared.
The aim was to move towards a clearer single source of truth, where data is transformed and governed once, then made available to authorised users through a consistent, Data Marketplace model.
This addressed the root causes of complexity: duplicated effort, inconsistent governance and fragmented access to data across the organisation and the wider Group.
How the roadmap worked in practice
Working with Dufrain, the team developed a practical roadmap grounded in delivery.
A core principle underpinned the approach: do not wait for a perfect target state. Instead, the team simplified the estate, solved real integration challenges and made progress visible while architectural and governance questions were still evolving. In practice, that meant building momentum through live work and creating a clearer view of what good could look like for the wider Group.
- A clearer, federated data architecture
Creating a stronger foundation for data products, analytics and reporting, while improving alignment with Group data strategy. - A modern lakehouse foundation. Introducing a governed lakehouse approach including AWS technology, including SageMaker Lakehouse, to support trusted analytics and future capability. This is positioned as one of the first deployments of SageMaker Lakehouse in this environment, helping turn Group data strategy into live implementation and providing early learning for what comes next.
- A simpler technology footprint
Creating a path to decommission older platforms and reduce the overall technology footprint — lowering operational overhead, reducing risk and freeing up capacity for higher‑value delivery. - Trust and Control by Design
Ownership, access, quality, and control are embedded into the operating model from the outset, ensuring governance as an inherent capability rather than a separate compliance activity.
the outcome
The programme is already delivering meaningful benefits:
- Greater consistency and confidence
A single, trusted foundation reduces reconciliation effort and gives teams greater confidence that they are working from the same data. End-to-end data classification and tagging has also established a central governance layer, enabling secure, controlled data access across the AWS environment.
- Reduced operational drag
Reducing reliance on multiple architectures lowers duplication, simplifies support and helps free engineering capacity for higher-value delivery. More than 17 operational data sources are now held and served from a single AWS-based environment, creating a more scalable foundation for the team.
- Clearer access across NatWest Group
Data is becoming easier for authorised teams to understand, access and reuse — supporting analytics, regulatory reporting and broader consumption across the Group. Standardised datasets in the lakehouse also create a stronger foundation for sharing data products more consistently across platforms, including AWS and Snowflake.
- Stronger customer journey insight
Better-connected data improves visibility of how customers engage over time and supports a clearer view of progression into NatWest products and services. A near real-time ingestion architecture, with delta loads approximately every 15 minutes for key services such as payment, ledger and subscriptions, also supports a wider range of operational and analytical use cases.
- Readiness for future needs
The foundations support current regulatory requirements, including FSCS, while positioning the estate for future analytics and innovation without further major redesign. The use of open, interoperable data structures also supports a scalable data product strategy and emerging AI-driven capabilities over time.
Together, these outcomes have increased confidence in the data, the platforms and the team’s ability to keep moving as complexity grows. The work is still progressing, but the direction is clearer and the foundations are stronger.
Minimal overhead, maximum delivery focus
Several ways of working helped keep delivery moving, even as complexity increased:
- Lead through delivery, not theory
Visible progress created momentum and confidence while architectural and governance questions were still being resolved. - Move early and learn fast
Trialling new patterns in live delivery surfaced real learning and reduced uncertainty for what followed. - One multidisciplinary team working towards the same goal
Close alignment across engineering, analytics, governance and delivery reduced friction, helped shape solutions around real user needs, and allowed decisions to move faster.
Partner contribution
The team worked with partner Dufrain to help shape and deliver a roadmap that balanced pace with governance and long-term value.
Dufrain brought experience of working across complex, regulated environments, supporting the team to navigate architectural, governance and integration challenges while keeping delivery practical and moving. The partnership was deliberately hands‑on, with shared ownership and a strong focus on turning strategy into live delivery.
What this shows
This work shows that large‑scale, complex data transformation can move at pace when the goal is clear and teams stay focused on outcomes, not perfect planning.
Progress came from moving early, simplifying the estate, testing new approaches and making tangible improvements visible – rather than waiting for every dependency or future target state to be fully defined. In doing so, the work provides a useful example of how similar ambitions can be translated into practice.
It also demonstrates the value of working with partners who understand how to accelerate delivery inside a regulated, enterprise environment, without adding unnecessary complexity.
Just as importantly, it shows what’s possible when teams work together. When engineering, analytics, governance and delivery stay aligned, silos reduce, bottlenecks ease and momentum builds.
Taken together, this work provides a clear example of how pace, control and scale can work together and a strong foundation for continued progress across the business and its connectivity into the wider Group.
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