AXP Data Architect

The Data Architect is a specialized technical architect responsible for designing, governing, and operationalizing the data architecture for all  exposure and engagement events flowing from AXP channels.

Key Responsibilities

• Own the end-to-end data architecture for the AEP exhaust pipeline: from channel exposure events (Sent, Delivered, Clicked, Opened, Disposition) through AEP Events Processing → Kafka Event Stream → Upstream
• Design event schema and XDM
• Architect the AEP Events Processing layer: validate, enrich, deduplicate exposure events from all channels (Email, SMS, Push, In-App, Web, Direct Mail, Call Center) and ensure correct propagation
• Design the Kafka event stream topology including topic design, partitioning strategy, retention policies, and at-least-once delivery guarantees
• Define the data contract between AEP Events Processing and upstream AI/ML structure - schema, envelope structure, delivery SLAs, and error handling
• Establish data governance, lineage, and observability standards for the exhaust pipeline: schema registry, data quality checks, alerting, and reconciliation
• Partner with the AEP Architect, AJO Architects, and Integration Team to ensure exposure event capture is embedded in all channel journey designs from the start
• Support CJA Architect in ensuring exhaust event schema richness for cross-channel attribution, experimentation, and reporting use cases
• Lead architecture documentation, data dictionaries, and technical standards for the exposure event domain

Core Skills

• Data architecture: event schema design, XDM, data contracts, data lineage, governance
• Kafka and event streaming: topic design, partitioning, retention, consumer patterns, DLQ
• AEP Events Processing and AXP Streaming API
• API design: REST, event envelope standards, retry/error handling patterns
• Real-time data pipeline architecture (streaming, micro-batching)
• Data quality, observability, and schema registry management
• Cloud data platform experience (AWS, Azure, or Google Cloud Platform)

Typical Experience

• 8–12+ years in data architecture, data engineering, or integration architecture
• Deep experience with event-driven architectures and streaming data platforms (Kafka preferred)
• Hands-on experience with AEP data model, XDM, and streaming ingestion
• Experience designing real-time feedback loops between MarTech platforms and decisioning/ML systems preferred
• Exposure to CDP, NBA, or personalization platform architectures a strong plus