• Engineer and validate consumer-level attributes from credit bureau and alternative data sources • Apply statistical techniques to uncover insights and improve predictiveness • Monitor attribute performance for stability, compliance, and accuracy • Build dashboards and visualizations (Tableau) to communicate findings • Collaborate with engineering to productionalize prototypes into scalable solutions • Partner with product, risk, and business teams to maximize impact across marketing, risk assessment, and collections • Engage with clients to explain analytics and translate technical results into applicable business insights

• Lead Experian's platform engineering modernization by unifying global engineering practices through automation and self‑service, not mandates. • Architect and scale an Automated Service Catalog that delivers standardized, lifecycle‑managed services via a frictionless, "path of least resistance" experience for engineers across LATAM, North America, UK&I, and EMAP. • Convert a conceptual global vision into a clear strategy, roadmap, operating model, and governance adopted across regions. • Design and launch a one‑click self‑service catalog for standardized, API‑driven services. • Apply AI/agentic automation to decisioning to convert days/weeks into minutes. • Establish a federated contribution model for developers globally to publish, validate, and reuse automations. • Partner with Security, Cloud, Engineering, Architecture, Data, and Product to simplify architectures and unify standards that can be automated. • Build continuous feedback loops with engineering teams; iterate for measurable outcomes.

• The Lead Azure Data Engineer is responsible for migration, governance, and data integration for the implementation of new Microsoft Cloud based document routing and task management system. • They will ensure alignment with the technical, security, and document management requirements such as leading data discovery and mapping, validating metadata standards, managing data migration into Dataverse and SharePoint Online, and ensuring proper implementation of retention, auditability, and role-based access controls within the Microsoft SaaS architecture.

• Design, build, and optimize high-volume, high-performance ELT pipelines for centralized data warehousing • Collaborate with Product Managers, ML Engineers, Data Scientists, and DevOps to define and enforce a reliable, scalable, and secure data platform architecture • Ensure adherence to data warehousing standards, data quality best practices, and metadata management processes • Take ownership of key data warehouse components and drive improvements in performance and reliability • Conduct architecture reviews and participate in system design discussions to provide technical leadership • Mentor and guide junior engineers, fostering a culture of quality and continuous learning