Chinelle Clarke
Executive Consultant
Digital Marketing Data Architect
United States of America (USA)
Apply by 1 Feb 2026
100.0 - Per Hour
Job Ref.: 56045
Job Type: Contract
Job Description
I. Overview
We are seeking an experienced and highly specialized Digital Marketing Data Architect to lead the design and implementation of Enterprise Data Warehouse (EDW) data model, with a critical focus on integrating and utilizing data from Adobe Analytics and other core digital marketing systems.
This role is essential for transforming raw digital interaction data into a unified, campaign-ready data model that will directly power customer segmentation, campaign management, and marketing effectiveness reporting. The ideal candidate is a hybrid professional with strong data architecture skills and deep expertise in digital marketing principles and Adobe data collection nuances.
II. Key Responsibilities
Architecture & Modeling
- Adobe Analytics Data Modeling: Act as the Subject Matter Expert (SME) to design, validate, and enhance the conceptual, logical, and physical data models for all Adobe Analytics data feeds (including Data Warehouse and/or Data Feeds).
- Campaign Data Integration: Architect the integration of data from various sources including Adobe Analytics, Sitecore (Content Management), and ECID (Experience Cloud Identity Service) into the EDW to create a unified Customer 360 view for campaign use.
- Documentation & Validation: Lead the review, validation, and enhancement of existing data model, Business Requirements Document (BRD), and System Design Architecture (SDA) documents to ensure alignment with current marketing campaign objectives.
- Data Governance: Define standards and best practices for data quality, data lineage, metadata management, and data usage policies for all marketing and campaign data within the EDW.
- Campaign Enablement: Design data structures that support advanced marketing use cases such as audience segmentation, personalization, campaign attribution, and lift analysis.
- Channel and Tagging Expertise: Advise on the proper mapping and modeling of key digital marketing concepts, including UTM Tags, search engine data, social media interaction data, and other channel-specific tracking parameters.
- SEO/Digital Insights: Ensure the data model captures the necessary granularity to support analysis on Search Engine Optimization (SEO) performance and the effectiveness of different marketing channels.
- Sitecore & ECID: Ensure data integration from Sitecore is correctly mapped to customer profiles using the ECID to achieve a persistent, cross-channel customer identity.
- Collaborate closely with Data Engineers on ETL/ELT pipeline design, ensuring efficient and accurate data ingestion and transformation from source systems to the target EDW model.
- Work with Marketing/Campaign Managers and Business Analysts to translate high-level campaign requirements into technical data specifications.
- Provide technical leadership and mentorship on digital marketing data practices to the broader data and analytics teams.
Technical Expertise
- 8+ years of experience as a Data Architect, Data Modeler, or a similar role focused on Enterprise Data Warehousing.
- Deep, hands-on expertise with Adobe Analytics (specifically its data export/data feed structure, eVars, props, and event data).
- Note: Experience modeling Adobe Analytics data for an external data warehouse is highly critical.
- Extensive knowledge of Digital Marketing/Campaign Management concepts (e.g., attribution models, conversion funnels, A/B testing data, customer journey analysis).
- Thorough understanding of digital tracking standards, including UTM parameters, cookie/identity management, and the difference between session, visitor, and hit data.
- Familiarity with the types of data generated by and collected from social media platforms and how to model that data for campaign effectiveness.
- Excellent communication skills with the ability to bridge the gap between technical teams and non-technical marketing stakeholders.
- Proven ability to lead technical design sessions, challenge existing assumptions, and drive consensus on data architecture decisions.
- Exceptional analytical and problem-solving skills to troubleshoot complex data integration and modeling challenges.