Data Architect

Quick Facts

• Role: Data Architect (AI-focused)

• Focus: Secure, real-time data architecture for AI/ML workloads in fleet and vehicle payment solutions

Description

Design and evolve robust data architectures that enable intelligent analytics, machine learning, and AI-driven capabilities such as fraud detection, risk scoring, spend optimization, and predictive vehicle insights. You will plan end-to-end data architectures covering data modeling, canonical schemas, scalable pipelines, feature engineering, and model-ready datasets for AI/ML deployment. The role also includes governance and compliance for PCI/GDPR financial data, plus architectural guidance for APIs, microservices, and event-driven systems.

Responsibilities

• Plan end-to-end data architectures for AI and ML using structured, semi-structured, and unstructured data

• Develop data models, canonical schemas, entity definitions, and integration approaches for international vehicle payment workflows

• Build scalable data pipelines for ingestion, transformation, feature engineering, and model deployment

• Define long-term data architecture strategy aligned to the platform roadmap

• Ensure support for explainable AI, responsible AI, and transparent model evaluation

• Collaborate with data science teams on a unified feature store, ML registry, and model-ready datasets

• Implement real-time and near-real-time flows for fraud detection and authorization decisioning

• Evaluate and recommend AI/ML technologies such as vector stores, model operations platforms, and data platforms

• Enable secure integration of generative and predictive AI into customer and operator-facing solutions

• Establish data quality, lineage, metadata, and cataloging standards

• Partner with security and compliance teams for PCI, GDPR, and financial services data requirements

• Define policies for data retention, PII handling, model transparency, and AI governance

• Work 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, 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 and data lake/lakehouse architectures

• Understanding of streaming platforms, feature stores, and model serving patterns

• Understanding of MLOps practices (ML CI/CD, automated retraining, 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

Benefits

• Up to 26 business vacation days per year

• 10 illness/special days off per year (fully paid)

• Health and life insurance (Luxmed)

• MyBenefit platform with Multisport option

• Internal psychological support service

• English language classes from the first working day

• Access to external learning platforms (O’Reilly, LinkedIn Learning, Udemy) and internal training catalog

• Flexible workplace: office, home, or hybrid

• Tech Skills Mentoring Program

• Opportunities to develop as a public speaker, mentor, or technical interviewer

• Fully paid bench time when not involved in a project

• Certification reimbursement (AWS, GCP, Microsoft, etc.)