Architect

Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.

Job Description

About the Role:

We are looking for a Staff Architect to join our Data & AI Platform Architecture team. We are a small, high impact group that shapes technology strategy across analytics products, AI/ML enablement, and data infrastructure at enterprise scale.

This is a role for a builder-architect, someone with deep fundamentals in data, analytics, and MLOps platforms. You are equally comfortable evaluating build-vs-buy tradeoffs, integrating commercial platforms where they're the right tool, and building the missing primitives yourself when they're not.

You reason from fundamentals about how data moves within an organization, and how value is generated from it. You understand how organizations have traditionally made data usable for human users and how to extend it to be usable by AI agents.

You will sit within a global team chartered to build global data products and the mechanisms that make cross-border workflows possible. You will lead how we make regional data usable across borders by applying semantic and ontology standards across regions, and entity resolution that connects regional data without centralizing it.

You will report to the Sr. Director of Platform Engineering. This is an individual contributor position.

What you'll do here

• Develop the mechanisms that make cross-border data products possible by privacy-preserving techniques, derived signals that can cross borders, and shared semantics
• Build cross-border entity resolution as the foundational capability underneath those products, working with our data science teams on matching approaches and match quality.
• Build the layers that make our data consumable by agents with semantics and ontologies across regions, governed discovery, and access paths that keep usage accurate, and compliant.
• Guide technology adoption across engineering teams through reference implementations and reusable patterns that teams adopt
• Lead focused prototyping and R&D efforts with product and engineering teams to validate new Data & AI capabilities
• Mentor engineers across the organization in your areas of expertise, with a focus on fundamentals thinking, system design, and product awareness.