Senior Director, Data & Identity Architect

at Acxiom in Augusta, Maine, United States

Acxiom is seeking for an experienced and technical leader in its Product & Engineering group to lead the design and development of its next-gen Data & Identity product family. This role will drive the modernization of our identity resolution and data sharing platforms by harnessing cloud-native technologies, privacy-enhancing computation and agentic orchestration. You will be responsible for advancing capabilities in digital and terrestrial identity recognition, cross-channel tagging, and machine learning-based match accuracy, while ensuring compliance with PCI , HIPAA , FCRA , CCPA , and GDPR .

This is a high-impact opportunity to architect the next-generation identity backbone supporting personalization, analytics, media activation, and data collaboration in a privacy-centric world.

*This role ca be located almost anywhere in the U.S.

What You Will Do:

+ Design next-gen data & identity products through cloud-native, real-time platforms using microservices, containerization, and serverless frameworks.

+ Architect a persistent identity infrastructure to manage hundreds of billions of identifiers, enabling unified views of customer journeys across digital, terrestrial (offline), and hybrid touchpoints.

+ Build intelligent systems for digital recognition (web, app, CTV ) and terrestrial recognition (in-store, call center, IoT) using device signals, hashed identifiers, and contextual tags.

+ Design channel-aware tagging frameworks that capture behavioral, transactional, and metadata signals across owned and paid media, enhancing identity linkages and customer intelligence.

+ Implement advanced machine learning models for probabilistic matching, linkage scoring, and graph-based learning to continuously improve identity resolution accuracy.

+ Leverage AI agents and agentic flows to dynamically orchestrate data matching, validation, and enrichment based on consent rules, user context, and platform intelligence.

+ Drive experimentation with reinforcement learning, active learning, and feedback loops to optimize customer match rates and reduce false positives.

+ Design secure, interoperable identity capabilities within clean room environments (e.g., Snowflake, AWS , Databricks) for multi-party data collaboration.

+ Develop frameworks for pseudonymization, encryption, and federated data analysis to enable compliant, large-scale audience modeling and media measurement.

+ Enforce data governance standards for consent management, opt-in/opt-out, zero trust,