Data Architect

Job Title: Data Architect

Job Location: London, UK/Hybrid

Job Type: Permanent

Key Responsibilities

Data \& AI Architecture

• Design end to end data architectures to support AI/ML workloads, including structured, semi structured, and unstructured data.


• Develop data models, canonical schemas, entity definitions, and integration patterns for international vehicle payment systems.


• Architect scalable data pipelines supporting ingestion, transformation, feature engineering, and model deployment.


• Define the long\-term data architecture strategy aligned with International Vehicle Payments technology roadmap.


• Ensure data architectures support explainable AI, bias management, and transparent model performance.

• Collaborate with Data Science teams to create a unified feature store, ML registry, and model ready datasets.


• Implement real time/near real time data flows required for fraud detection and authorization decisioning.


• Evaluate and recommend AI/ML technologies, vector databases, model ops platforms, and data platforms.


• Enable secure integration of generative AI and predictive AI in customer\- and operator\-facing use cases.

• Establish data quality, lineage, metadata, and cataloguing standards.


• Partner with Security and Compliance teams to ensure adherence to PCI, GDPR, and financial services data standards.


• Define and enforce policies on data retention, PII handling, model transparency, and AI governance.

• Work closely with software engineering teams to embed data centric design into product architecture.


• Provide architectural guidance for APIs, microservices, and event\-driven systems powering vehicle payments.


• Conduct architectural reviews, create reference architectures, and mentor engineers.


• Drive continuous improvement of data reliability, scalability, and cost efficiency.

• 10\+ years in data architecture, solution architecture, or similar roles.


• Strong experience designing cloud\-native data platforms (AWS preferred).


• Deep knowledge of: Distributed data processing, Data\-lake/Lakehouse architectures, Streaming platforms \& Feature stores and model serving.


• Understanding of ML Ops practices (CI/CD for ML, automated retraining, monitoring).


• Proven experience supporting or architecting AI/ML\-driven products.


• Strong understanding of security and regulatory controls for financial data.


• Ability to communicate clearly with technical and non\-technical stakeholders.

• Experience in payment processing, fleet/vehicle telematics, or financial services.


• Familiarity with vector databases and LLM\-based architectures.


• Exposure to real\-time fraud detection systems.


• Certifications in Azure Data/AI, Enterprise Architecture, or similar.


• Prior experience with enterprise\-scale modernization initiatives.

• Delivery of a scalable, reliable data and AI architecture aligned with business goals.


• Reduction in model deployment time and data preparation complexity.


• Improved real\-time insights for fraud detection, spend control, and vehicle payment workflows.


• Strong partnerships across Product, Engineering, Data Science, and Compliance.


• Demonstrated uplift in data quality, governance, and platform performance.

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