Senior Principal SAP Datasphere Architect

Role: Senior Principal SAP Datasphere Architect
Experience: 12–16+ Years

Location: Irving, TX (Onsite/Hybrid)
Visa: / GC

Experience Level: 12–16+ Years (Senior Leadership / Architecture)Focus: Enterprise Data Fabric & Advanced Cloud Modeling

Core Responsibilities: SAP Datasphere Artifact Development

As a Lead Architect, you will be responsible for the high-level design and hands-on governance of the following technical artifacts within the SAP Datasphere environment:

• Space Management & Governance:
  • Designing and configuring Spaces based on functional domains (e.g., Finance, Supply Chain, Retail) or regional requirements.
  • Managing resource allocation (Storage/Compute quotas) and defining User Roles and Scoped Permissions to ensure data security.
• Data Builder (Technical Layer):
  • Tables & Views: Creating complex Graphical Views and SQL Views to join, union, and aggregate data from disparate sources.
  • Data Flows & Replication Flows: Architecting high-performance Replication Flows for delta-loading from S/4HANA and Data Flows for complex ETL/Python-based transformations.
  • Intelligent Lookup: Implementing Intelligent Lookups to harmonize disparate datasets where a common key is missing.
• Business Builder (Semantic Layer):
  • Data Entities & Fact Models: Developing the business semantic layer using Business Entities, Fact Models, and Dimensions.
  • Consumption Blocks: Creating Consumption Blocks and Perspectives to expose refined data specifically for SAP Analytics Cloud (SAC) and Power BI.
• Advanced Integration:
  • Remote Tables: Configuring Remote Tables using SDI/SDA for real-time federated access to Snowflake, Azure SQL, or On-Premise HANA.
  • Analytic Models: Building high-performance Analytic Models with multi-dimensional capabilities, restricted measures, and variables for complex business logic.

Qualifications for 12–16 Years of Experience

• Strategic Leadership:
  • Proven track record of leading 3+ full-cycle SAP Datasphere or BW/4HANA implementations in a global, dual-shore environment.
  • Ability to translate 16+ years of retail/fashion domain expertise into scalable data models that solve specific industry challenges (e.g., inventory aging, cross-channel sales attribution).