SAP SAC with DATASPHERE

Role Summary
We are seeking a Senior SAP Analytics & Datasphere Architect to lead the modernization of our enterprise data landscape. You will be responsible for designing scalable cloud architectures that unify disparate data sources into a cohesive SAP Business Data Fabric. This role requires a strategic thinker who can bridge the gap between complex technical data modeling in Datasphere and high-impact executive storytelling in SAP Analytics Cloud (SAC).
Key Responsibilities
Architectural Leadership: Define and maintain the enterprise analytics roadmap aligning SAP Datasphere and SAC with business transformation goals.
Advanced Data Modeling: Design complex semantic layers star/snowflake schemas and analytical models within Datasphere.
Modernization & Migration: Lead Lift & Shift or Greenfield programs migrating legacy SAP BW/4HANA BEx or BPC environments to cloud-native architectures.
Multi-System Integration: Build robust data pipelines and replication flows across S/4HANA SuccessFactors and non-SAP sources like Snowflake or Azure.
Governance & Security: Implement Spaces Data Access Controls (DAC) and complex Role-Based Access Control (RBAC) to ensure data integrity and compliance.
Advanced Analytics: Develop sophisticated SAC stories analytical applications with custom scripting and complex SAC Planning models including Data Actions and Advanced Formulas.
Stakeholder Management: Lead workshops with C-suite executives to translate business requirements into technical KPIs and automated dashboards.
Required Skills & Qualifications
Overall Experience: 712 years in SAP BI/BW/HANA with at least 3 years specifically in SAP Datasphere and SAC.
Datasphere Expertise: Deep hands-on knowledge of Spaces Intelligent Lookups Task Chains and Replication Flows.
SAC Proficiency: Expert-level skills in Story Design Analytics Designer (scripting) and Predictive Scenarios.
Technical Foundations: Advanced SQL HANA Calculation Views and S/4HANA CDS Views.
Modern Data Stack: Familiarity with SAP BTP Data Intelligence or competitive platforms like Databricks and BigQuery is highly valued.
Project Delivery: Proven track record of leading 2 full-cycle end-to-end cloud implementation projects.