DATA Architect AEP

Role Overview:
An Adobe Experience Platform (AEP) Data Architect is responsible for designing and governing the data architecture required to collect, unify, manage, and activate customer data across Adobe Experience Cloud and other enterprise systems.

Key Responsibilities:

• Design end-to-end Adobe Experience Platform (AEP) data architecture based on business and technical requirements.
• Define XDM schemas, data models, datasets, identities, namespaces, and relationships.
• Design customer data ingestion architecture using batch and streaming ingestion.
• Implement and govern Identity Service and customer identity stitching strategies.
• Design Real-Time Customer Profile architecture and profile-enabled datasets.
• Develop data ingestion and integration patterns between AEP and systems such as CRM, web, mobile, data warehouses, and APIs.
• Define data governance, privacy, security, consent, and data-retention standards.
• Design Adobe Experience Platform data flows and integration patterns.
• Work with Adobe Experience Platform Launch/Tags, Adobe Analytics, Adobe Target, Journey Optimizer, Real-Time CDP, and other Adobe Experience Cloud solutions where applicable.
• Define audience segmentation and activation architecture.
• Collaborate with data engineers, developers, solution architects, business stakeholders, and marketing teams.
• Establish standards for data quality, monitoring, lineage, and troubleshooting.
• Review technical designs and ensure adherence to enterprise architecture standards.
• Provide technical leadership during AEP implementation, migration, and integration projects.
• Create architecture diagrams, data-flow diagrams, technical specifications, and implementation documentation.

Required Technical Skills

• Strong knowledge of Adobe Experience Platform (AEP)
• XDM / Experience Data Model
• Schema Registry
• Datasets and Dataflows
• Identity Service
• Real-Time Customer Profile
• Segmentation Service
• Data Governance
• Batch and streaming data ingestion
• REST APIs and event-based integrations
• SQL and data modeling
• JSON
• Cloud technologies and enterprise data platforms
• Understanding of ETL/ELT and data integration patterns