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. • 10+ years of software engineering experience, with a focus on data platforms, analytics infrastructure, and AI/ML systems • Bachelor's degree or higher in science, technology, engineering, or a related field. • Demonstrated first-principles reasoning about platform tradeoffs, able to explain at the mechanism level why a system behaves the way it does • Hands-on experience across the full data lifecycle, from ingestion to transformation, from delivery into BI and ML consumption • Experience with data modeling, schema design, and data quality as platform engineering concerns, building the systems that enforce lineage, catalog metadata, and governance policy at scale. • Experience designing architectures that deliver unified, governed access to data across systems • Demonstrated experience overseeing and evolving shared platform architectures, including setting boundaries, managing tradeoffs, and adapting designs • Experience with distributed computing and cloud-native infrastructure (Amazon Web Services preferred), including the cost and operational dynamics of running data workloads • Comfort with infrastructure as code and operating production workloads. • Hands-on experience with graph databases, entity resolution or record linkage systems Benefits/Perks: • Great compensation package and bonus plan • Core benefits including medical, dental, vision, and matching 401K • Flexible work environment, ability to work remote, hybrid or in-office • Flexible time off including volunteer time off, vacation, sick and 12-paid holidays • Explore all our exciting benefits here: yourexperianbenefits.com • #LI-Remote Our uniqueness is that we celebrate yours. Experian's people first, inclusive and purpose driven culture is multi award-winning; World's Best Workplaces™ 2025 (Fortune Global Top 25), Great Place To Work™ in 26 countries to name a few. Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education. This position is also eligible for a variable pay opportunity and a comprehensive benefits package. Experian's recruitment process is conducted only through authorised channels. Recruitment communications will only be sent from an @ experian.com email address. Experian will never ask candidates to make any payment as part of a recruitment process. To apply for roles or verify opportunities, please visit experian.com/careers . Experian is proud to be an Equal Opportunity Employer for all groups protected under applicable federal, state and local law, including protected veterans and individuals with disabilities. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

Requirements

Must-haves

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.
10+ years of software engineering experience, with a focus on data platforms, analytics infrastructure, and AI/ML systems
Bachelor's degree or higher in science, technology, engineering, or a related field.
Demonstrated first-principles reasoning about platform tradeoffs, able to explain at the mechanism level why a system behaves the way it does
Hands-on experience across the full data lifecycle, from ingestion to transformation, from delivery into BI and ML consumption
Experience with data modeling, schema design, and data quality as platform engineering concerns, building the systems that enforce lineage, catalog metadata, and governance policy at scale.
Experience designing architectures that deliver unified, governed access to data across systems
Demonstrated experience overseeing and evolving shared platform architectures, including setting boundaries, managing tradeoffs, and adapting designs
Comfort with infrastructure as code and operating production workloads.
Hands-on experience with graph databases, entity resolution or record linkage systems
Flexible work environment, ability to work remote, hybrid or in-office
Flexible time off including volunteer time off, vacation, sick and 12-paid holidays

Nice-to-haves

Experience with distributed computing and cloud-native infrastructure (Amazon Web Services preferred), including the cost and operational dynamics of running data workloads
Great compensation package and bonus plan

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiml

Platform: smartrecruiters
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401k