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
