Data Architect

dentsu•USA - Remote - Georgia, GA

9d•$113,000 - $160,000•Remote

About The Position

Merkle is seeking an experienced Data Architect to lead the design and delivery of product modernization initiatives for enterprise customers migrating legacy Adobe solutions to modern platforms across Analytics, Content, and Commerce domains. You will architect and operationalize the end-to-end data foundations that power our customers' digital marketing, content, and commerce ecosystems — spanning data strategy, modeling, integration, and governance across Adobe Experience Platform, content operations, crm systems, and commerce applications. As an enterprise data architecture, you'll design the schemas, pipelines, and governance frameworks behind secure, scalable solutions that support unified profiles, segmentation, journey orchestration, and campaign activation for our customers.

Requirements

8+ years of hands-on data architecture, data modeling, SQL development, and analytics platform experience working with enterprise customers.
Expert proficiency in crafting customer-centric database models, datasets (e.g., CRM, Call Center, Marketing, Offline, Point of Sale, etc.) with relational, hierarchical (e.g., RDBMS, Columnar, Data Warehouse, BI, Document, Semantic layer modeling, Data Lakes, OLTP & OLAP, etc.).
Demonstrated experience auditing, assessing, and documenting data components of implementations; ability to translate complex data configurations and data models into clear business requirements and technical documentation.
Advanced SQL skills including window functions, complex joins, aggregations, stored procedures, and query optimization for analytics workloads.
Hands-on experience with Adobe Experience Platform (AEP), including data ingestion, schema design, unified profiles, segmentation, real-time activation workflows, and native AI tools.
Knowledge of identity resolution, data privacy frameworks, and consent management in a multi-domain context.
Proficiency in API-first integration patterns (REST, webhooks, Postman) and basic scripting (Python or Bash) for data pipeline automation and validation.
Excellent written and verbal communication and strong organizational skills; proven ability to balance concurrent customer engagements and distill complex architectures and migration strategies for executive and technical audiences.

Nice To Haves

Adobe Certified Expert (ACE) in CJA or AEP Data Architect.
Adobe Certified Associate (ACA) in Real-Time Customer Data Platform or Analytics.
Hands-on experience with Adobe Experience Platform for Content or Commerce (Content Hub, Commerce product data, personalization).
Hands-on experience with Adobe Analytics API (Report API, Admin API) for automated assessment and documentation.
Experience with Analytics-to-CJA migration patterns, common reconciliation challenges, and metric mapping best practices.
Experience with version control (Git) and CI/CD practices for data solution deployment.
Track record of presenting modernization audits and migration strategies to C-suite and line-of-business stakeholders.

Responsibilities

Provide deep experience to build data solutions across multiple Adobe products and cloud platforms aligned with enterprise data strategy.
Engage closely with customers and Adobe team to facilitate data discovery by evaluating systems and business processes. Analyze customer sources, data movement, data granularity, relationships, data format, etc.
Unify disparate data (e.g., sales, CRM, analytics data, etc.) to meet customers’ digital marketing use cases. Lead and develop conceptual, logical, and physical data models for multi-solution delivery.
Showcase and follow frameworks for data quality, define standards, master data management, data services, data governance, data modeling, tools, data security, privacy, and compliance with industry regulations (PII, PCI, HIPAA, GDPR, etc.).
Engage with cross-disciplinary groups and Adobe professionals to identify customer demands. Provide data layout and strategic blueprints, advocating for scalable, secure resolutions. Assume the role of a liaison to promptly tackle technical obstacles.
Provide solutions for growing data volumes, tools, and integrations, while aligning to customers’ objectives.
Deliver Adobe platform data lake and real-time customer profile to get ready for data ingestion and activation. Employ REST APIs, Postman, and basic scripting to automate and streamline the implementation and setup.
Develop and construct data ingestion solutions for streaming and batch processing, online and offline data within AEP. Collaborate with data engineers to develop and implement ETL/ELT pipelines for data collection and extraction.
Improve data query performance across platforms by tuning models and adhering to guidelines and ensure product guardrails are followed and deployed in solutions
Drives end-to-end data migration initiatives, transforming and migrating large-scale datasets while maintaining data quality, integrity, and compliance.
Audit existing Adobe solutions to establish current state baseline and identify technical debt, governance gaps, and data quality issues.
Assess platform maturity: evaluate taxonomy consistency, content metadata tagging practices and standards compliance, and commerce product data enrichment levels; flag redesign opportunities prior to modernization.
Identify platform-specific reconciliation and integration points and document data consistency requirements.
Unify disparate data sources (CRM, call center, marketing, sales, content operations, commerce/order data) to meet customers' digital marketing, content, and commerce use cases within a single AEP foundation.
Map legacy platform infrastructure to AEP schemas and CJA data views; determine what migrates directly, what requires transformation, and what should be redesigned for improved governance and cross-domain insights.
Design AEP data models (conceptual, logical, physical) across Analytics, Content, and Commerce domains—including event schemas, entity relationships, attribute hierarchies, identity resolution, content asset structures, and product data models.
Develop relational and dimensional data models for analytics spanning multiple customer datasets (CRM, marketing, offline, point-of-sale, content, commerce) across RDBMS, columnar, data warehouse, and data lake environments.
Architect AEP data ingestion pipelines (streaming, batch, online, offline) across Analytics, Content, and Commerce data sources; collaborate with data engineers to build automated ETL/ELT workflows maintaining data freshness and quality.
Support end-to-end modernization migrations, preserving metric definitions, historical accuracy, content governance, and commerce data integrity through transition phases.
Develop validation and reconciliation documentation for legacy-vs-modern platform comparisons in pilot and production