Data Architect

About the Position

This role combines deep architectural expertise with hands on knowledge of AI/ML data pipelines. You will design robust, secure, real time data platforms that enable our client to deliver next generation international vehicle payment capabilities.

Responsibilities

• Plan end to end data architectures that support AI and ML workloads using structured, semi structured, and unstructured data
• Develop data models, canonical schemas, entity definitions, and integration approaches for international vehicle payment workflows
• Architect scalable data pipelines that handle ingestion, transformation, feature engineering, and model deployment
• Define long term data architecture strategy aligned with the platform roadmap
• Ensure the data architecture supports explainable AI, responsible AI, and transparent model evaluation
• Collaborate with data science teams to enable a unified feature store, ML registry, and model ready datasets
• Implement real time and near real time data flows for fraud detection and authorization decisioning
• Evaluate and recommend AI and ML technologies, vector stores, model operations platforms, and data platforms
• Enable secure integration of generative AI and predictive AI into customer and operator facing solutions
• Establish data quality, lineage, metadata, and cataloguing standards
• Partner with security and compliance teams to align with PCI, GDPR, and financial services data requirements
• Define and support policies for data retention, PII handling, model transparency, and AI governance
• Collaborate with software engineering teams to embed data centric design principles into product architecture
• Provide architectural guidance on APIs, microservices, and event driven systems
• Conduct architectural reviews, create reference architectures, and mentor engineers
• Drive improvements in data reliability, platform scalability, and cost efficiency

Requirements

• 10+ years of experience in data architecture, solution architecture, or related roles
• Experience designing cloud native data platforms in AWS
• Knowledge of distributed data processing, data lake and lakehouse architectures, streaming platforms, feature stores, and model serving patterns
• Understanding of ML operations practices including CI/CD for ML, automated retraining, and model monitoring
• Experience designing or supporting AI or ML based products
• Understanding of security and regulatory requirements for financial data
• Ability to communicate clearly with technical and non technical stakeholders

Nice to Have

• Experience in payment processing, vehicle telematics, or financial services
• Familiarity with vector databases and LLM based architectures
• Exposure to real time fraud detection systems
• Certifications in Azure Data or AI, Enterprise Architecture, or similar areas
• Experience with enterprise scale modernization programs