PwC
SAC- Manager
India · Work style not stated · Full time
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About the role
Description from the employer’s posting. Check the employer’s page for the current version.
- EmployerPwC
- LocationIndia
- Work styleWork style not stated
- Employment typeFull time
- Employer posted
Industry/Sector
Not Applicable
Specialism
Advisory - Other
Management Level
Manager
Job Description & Summary
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
Show full description
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
Travel Requirements
Not Specified
Job Posting End Date
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At a glance
- Employment typeFull time
- Employer posted
- Added to ROLIVA
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Skills in this posting
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