SAC- Manager

Role Overview

Lead end-to-end design and implementation of SAP Analytics solutions, with a strong focus on backend semantic modeling — building the data models and semantic layers within Datasphere/BW/4HANA/BDC that enable enterprise-wide analytics and decision-making, enriched with embedded AI (Joule) and complemented by SAP Analytics Cloud (SAC) reporting.

Key Responsibilities

• Lead end-to-end design and implementation of SAP Analytics solutions, with emphasis on the semantic and data modeling layer, embedded AI (Joule), and SAP Analytics Cloud (SAC) reporting
• Translate client requirements into scalable data models and semantic layers within SAP Datasphere, BW/4HANA, and SAP Business Data Cloud (BDC), including dimensions, hierarchies, calculation views, and reusable analytic models for enterprise-wide decision-making
• Design and optimize semantic layers (views, associations, currency/unit conversions, calculated and restricted measures) to ensure accurate, performant, and reusable analytic models
• Lead workshops to gather requirements, define KPIs, and translate them into well-structured backend models and metrics
• Guide teams in modeling data consistently across Datasphere, BW/4HANA, and BDC under a unified semantic strategy, ensuring model reusability and minimizing redundant logic
• Apply functional expertise across R2R, SD, P2P, Supply Chain, and other areas to ground data models and KPI definitions in real business processes
• Manage project timelines, deliverables, and stakeholder expectations across modeling and analytics modernization engagements
• Collaborate with clients to strengthen model governance, naming conventions, and data quality validation within the semantic layer
• Drive adoption of embedded AI/ML in modeling — including Joule-assisted model documentation, natural-language querying, and intelligent recommendations for model design
• Leverage SAP Business Data Cloud, Databricks, and Snowflake as governed data sources, designing semantic models that federate or harmonize data across these platforms
• Build and maintain SAP Analytics Cloud (SAC) reports, dashboards, and stories, leveraging modeled data and embedded AI (Joule) to deliver actionable, enterprise-wide insights
• Ensure data security, access governance, and regulatory compliance are embedded at the model level (row/column-level security, data access controls)
• Contribute to practice-building through COE assets and reusable accelerators — modeling templates, KPI/metric libraries, and semantic layer design standards
• Proactively identify, escalate, and mitigate project and technical risks
• Create and present solution architecture, modeling design documents, and executive summaries

What You Must Have

• At least a Bachelor's degree
• At least 9–13 years of experience
• Oral and written proficiency in English required

What Sets You Apart

• One or more SAP certifications in Analytics or Data Modeling — SAP Datasphere, SAP BW/4HANA, or related credentials
• Deep hands-on expertise in data modeling within SAP Datasphere and BW/4HANA (InfoObjects, ADSOs, CompositeProviders, graphical/scripted views), with working knowledge of SAP Business Data Cloud
• Working proficiency in SAP Analytics Cloud (SAC) reporting — building stories, dashboards, and visualizations to validate and showcase modeled data
• Strong experience designing semantic layers — dimensions, hierarchies, calculated/restricted key figures, currency conversions — that translate business requirements into robust analytic models
• Functional exposure to one or more core workstreams — R2R, SD, P2P — enabling context-rich model and KPI design
• Working knowledge of modeling across hybrid/multi-source landscapes (SAP and non-SAP), including federation or integration with Databricks and Snowflake-backed data
• Excellence in complex data analysis and model performance optimization
• Comfort embracing change and driving innovation in modeling-led analytics consulting, particularly around emerging capabilities like Joule and agentic AI for model design
• Developed skills in semantic model governance, access control, and data quality validation at the modeling layer
• Proven ability to mentor and upskill teams in modern SAP data modeling and analytics solutions