Senior Digital Experience Data Architect

Adobe•San Jose, NY

About The Position

Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! Opportunity As a Senior Digital Experience Data Architect at Adobe, you will lead the development of advanced, secure data solutions for our innovative digital marketing platforms. We craft data strategy, architecture, SQL and governance for customer solutions, including end-to-end profiles, segmentation, journeys, and campaigns!

Requirements

Degree in Computer Science, Information Systems, Data Science, or a related field or equivalent experience.
10+ years of data architecture, modeling, SQL, and working with 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.).
Advanced skills in SQL development (e.g., functions, data transformations, arrays, joins details, stored procedures, data analysis).
Deep experience in translating business requirements into scalable data architecture by conducting structured analysis of data workflows and processes
Demonstrate outstanding organizational skills and ability to balance customer projects concurrently with strong verbal, written communication skills and previous experience with customer-facing engagements

Nice To Haves

Hands-on use or administration of Adobe Experience Platform (AEP)
Deep domain expertise in one or more industries (Retail, Telecom, Healthcare, Automotive, Cloud and Streaming platforms, etc.)
Experience with programming languages (e.g., Python or Bash scripting)

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.
Establish 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.).
We develop and champion data architecture guidelines via detailed documentation. These encompass architectural blueprints, ERDs, data flow diagrams, source-to-target mappings, data dictionaries, metadata catalogs, governance frameworks, guardrails, and security and compliance protocols.
We engage with cross-disciplinary groups and Adobe professionals to identify customer demands.
We provide data layout and strategic blueprints, advocating for scalable, secure resolutions.
Assume the role of a liaison to promptly tackle technical obstacles.
We develop strategies for growing data volumes, tools, and integrations, while aligning with customers’ objectives.
We deliver mentorship on data architecture to customers and consultants to align work with targets.
We 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.
We improve data query performance across platforms by tuning models and adhering to guidelines and ensure product guardrails are followed and deployed in solutions